Techniques are disclosed for implementing cross-zone communication for computing zones executing different coding protocols. A server computer system may receive, via a proxy layer of a first instance of an application executing within a first computing zone according to a first set of coding protocols, a request for a service executed via a second instance of the application in a second computing zone according to a second, different set of coding protocols. The system may alter, via a remote layer of the first instance, a set of data specified in the request to comply with the second, set of protocols. The system may transmit, via the remote layer of the first instance to a remote layer of the second instance, the altered set of data. The system may advantageously provide a simplified development interface allowing for both development and testing within a local environment without deployment of multiple different services.
A method for operating a graph database, including receiving, by a computer system, a query to a particular graph database, the query identifying a plurality of vertices of the particular graph database. The method further includes performing, by the computer system, hash operations on two or more of the plurality of vertices to generate respective hash values and dividing, using the respective hash values, the query into a plurality of sub-queries, each corresponding to a subset of the plurality of vertices. The method also includes sending, by the computer system, ones of the plurality of sub-queries to a plurality of database repositories for the particular graph database.
A framework is provided for facilitating token sharing with contract issuers based on processing of smart contract transactions. The framework allows one or more computer nodes within a blockchain network to opt-in to a token sharing agreement with a contract issuer and a mechanism for an opted-in computer node to share tokens with the contract issuer in a decentralized manner by executing a smart contract and performing a set of computer procedures that is non-productive to the processing of the smart contract transaction. The execution of the set of non-productive computer procedures provides an additional amount of processing fee based on the processing of the smart contract transaction. The computer node then transfers a portion of the additional amount of processing fee to an account of the contract issuer as part of the processing of the smart contract.
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
H04L 9/36 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité avec des moyens pour détecter des caractères non destinés à la transmission
4.
GRAPH-BASED FEATURE ENGINEERING FOR MACHINE LEARNING MODELS
Methods and systems are presented for assisting a user to identify and evaluate features for use in a machine learning model configured to perform a task. Based on graph data associated with a graph data structure, a user interface is provided on a device. Based on user inputs received via the user interface, a feature candidate for the machine learning model is determined. The feature candidate is associated with a particular way of traversing the graph data structure to obtain attribute values associated with one or more vertices and/or one or more edges in the graph data structure. Based on the attribute values, a value corresponding to the feature candidate can be calculated. The value can be used to evaluate the effectiveness of the feature candidate in performing the task. The feature candidate can then be incorporated into the machine learning model as one of the input features.
Methods and systems are presented for providing a framework for facilitating time-sensitive cryptocurrency transactions for users. When a request for processing a time- sensitive cryptocurrency transaction using funds from a cryptocurrency wallet is received from a user, a transaction system first verifies whether the cryptocurrency wallet has a balance to cover the cryptocurrency transaction. The transaction system also verifies the ownership of the cryptocurrency wallet based on an asynchronous method. The user generates verification data without any input from the transaction system, and based on a private key associated with the cryptocurrency wallet, a generator function, and a user-generated value. Without knowing the user-generated value, the transaction system verifies the ownership of the cryptocurrency wallet based on the verification data, and processes the transaction for the user.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
6.
REDUCING FALSE POSITIVES IN ENTITY MATCHING BASED ON IMAGE-LINKING GRAPHS
Methods and systems are presented for performing comprehensive and accurate matching of user accounts with one or more known entities based on image-linking graphs. Images related to each known entity are retrieved from one or more online sources. Faces are extracted from the images. Based on attributes of the faces in the images, an image-linking graph is generated for the entity. When a user account is determined to be a potential match for the entity based on text-based attributes, an image associated with the account may be obtained. If the image matches with any one of the faces in the image-linking graph, an action is performed to the user account based on a position of the matched face in the image-linking graph.
G06V 40/16 - Visages humains, p.ex. parties du visage, croquis ou expressions
G06F 16/901 - Indexation; Structures de données à cet effet; Structures de stockage
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06V 20/30 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans les albums, les collections ou les contenus partagés, p.ex. des photos ou des vidéos issus des réseaux sociaux
G06Q 50/00 - Systèmes ou procédés spécialement adaptés à un secteur particulier d’activité économique, p.ex. aux services d’utilité publique ou au tourisme
7.
VERIFICATION SYSTEM FOR PROVING AUTHENTICITY AND OWNERSHIP OF DIGITAL ASSETS
Methods and systems described herein may implement blockchain asset authentication. A verification system may generate an encryption key associated with a digital asset, wherein the digital asset is associated with a first entity. The verification system may sign the digital asset using the encryption key. The verification system may generate a first key and a second key based on the encryption key, wherein the first key and the second key are part of a set of multi-party secret keys. The verification system may send the first key to the first entity and store the second key on the verification system. The verification system may receive a request to authenticate the digital asset. The verification system may in response to the request to authenticate, generate the encryption key based on the first key and the second key. The verification system may authenticate the digital asset based on the recreated first secret.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06F 21/64 - Protection de l’intégrité des données, p.ex. par sommes de contrôle, certificats ou signatures
8.
HOT WALLET PROTECTION USING A LAYER-2 BLOCKCHAIN NETWORK
Methods and systems for digital hot wallet protection are provided. A payment channel is established via a Layer-2 network of a cryptocurrency blockchain for transferring a cryptocurrency balance from a first digital wallet of a service provider to a second digital wallet of a trusted entity over a plurality of commitment transactions. A transaction receipt for each commitment transaction is transmitted to the trusted entity via a secure communication channel previously established between the service provider and the trusted entity outside of the Layer-2 network. A transaction log of the service provider is modified so that it no longer represents the current transaction state of the payment channel. Responsive to detecting a breach of the first wallet, a transaction is broadcast to a Layer-1 network of the blockchain for transferring the total cryptocurrency balance from the first wallet to the second wallet.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 50/18 - Services juridiques; Maniement de documents juridiques
Techniques are disclosed relating to automatically determining image quality for images of documents. In some embodiments, a computer system receives an image of a document captured at a user computing device. Using a neural network, the computer system analyzes the image to determine whether the image satisfies a quality threshold, where the analyzing includes determining whether one or more features in the image used in an authentication process are obscured. The computer system transmits, to the user computing device, a quality result, where the quality result is generated based on an image classification output by the neural network. Automatically determining whether a received image of a document satisfies a quality threshold may advantageously improve the chances of a system being able to complete an authentication process quickly, which in turn may improve user experience while reducing fraudulent activity.
G06V 10/776 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source Évaluation des performances
Methods and systems are presented for providing a framework for facilitating offline cryptocurrency transactions. A first application executed in a first secure enclave of a first device can register itself with a cryptocurrency computer network for initiating offline cryptocurrency transactions and reserve a denomination of cryptocurrency for the offline cryptocurrency transactions based on a token. The first application initiates an offline cryptocurrency transaction with a second application executed in a second enclave of a second device by transmitting a request comprising the token via a peer-to-peer connection. The second application verifies the request based on the token and attributes associated with the first application and the first secure enclave. Upon accepting the request, the second application stores the token in the second secure enclave. When a connectivity with a distributed ledger is available, the second application commits the offline cryptocurrency transaction to the distributed ledger.
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
G06Q 40/04 - Transactions; Opérations boursières, p.ex. actions, marchandises, produits dérivés ou change de devises
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
11.
NON-FUNGIBLE TOKEN (NFT) PURCHASE AND TRANSFER SYSTEM
Methods and systems for enabling off-chain transactions via a non-fungible token (NFT) marketplace are provided. A plurality of digital wallets associated with a service provider are provided with access to the NFT marketplace. The NFT marketplace corresponds to a decentralized blockchain associated with an entity that is different from the service provider. A request to perform a transaction involving a purchase, via the NFT marketplace, of an NFT associated with a specified source address is received from a first user of the service provider associated with a first identifier and a first digital wallet. Responsive to determining that the specified source address corresponds to a second user of the service provider associated with a second identifier and a second digital wallet, an identifier associated with the NFT is updated from the second identifier associated with the second user to the first identifier associated with the first user.
G06Q 40/04 - Transactions; Opérations boursières, p.ex. actions, marchandises, produits dérivés ou change de devises
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
Techniques are disclosed relating to automatically generating and analyzing database queries. In various embodiments, a database inquiry assistance system maintains a first machine learning model trained using query history data for a database and a second machine learning model using analysis history for the database. In an embodiment, the system receives from a user system a request for an inquiry into data stored in the database and identifies a sequence of queries for responding to the request, where identifying the sequence of queries includes applying the second machine learning model to the request. The system generates corresponding database query code for implementing one or more of the queries in the sequence of queries, where generating the corresponding database query code includes applying the first machine learning model to descriptors of one or more of the queries, and sends a plan identifying the sequence of queries to the user system.
Methods and systems are presented for providing explainable artificial intelligence for a deep-learning model on a global level. Multiple surrogate models are generated based on characteristics of the deep-learning model, where each surrogate model is configured to mimic a behavior of the deep-learning model with respect to one of the output dimensions associated with the deep-learning model. Simulations are performed on the surrogate models. Based on the simulation results, importance scores are calculated for each input feature of the deep-learning model. An importance score calculated for an input feature represents an extent to which the input feature contributes to a corresponding one of the output dimensions associated with the deep-learning model. The importance scores may then be used to modify the characteristics of the deep-learning model or other downstream machine learning models.
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p.ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
Methods and systems described herein may implement blockchain cryptocurrency transactions in a variety of environments. An online transaction processor may provide operations for cryptocurrency conversions. The transaction processor may detect that a user is involved in a cryptocurrency transaction with another entity, which is requested to be processed using an amount of cryptocurrency and using an off-chain amount of the cryptocurrency. The transaction processor may determine that the entity does not have a digital wallet, node, or the like on a layer two network to receive and/or process the off-chain balance for the cryptocurrency. The transaction processor may then, after a risk assessment, determine that the user may access the amount of the cryptocurrency from an on-chain balance available to a digital wallet of the cryptocurrency. The transaction processor may make that on-chain amount available and may request repayment via the user's off-chain balance.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
15.
INTERFACE FOR CONSTRUCTING SMART PROTOCOLS FOR EXECUTION ON BLOCKCHAIN PLATFORMS
A method for generating a smart protocol includes providing, by a server computer system, a user interface to one or more of a plurality of users. The server computer system may receive, via the user interface, input specifying terms corresponding to a smart protocol that is to be deployed on a particular blockchain platform. The specified terms may include the plurality of users associated with the smart protocol and a web resource to be used to identify one or more external data. An execution of the smart protocol may be based on a value of the external data. Based on the specified terms, the server computer system may generate, without further input from the plurality of users, the smart protocol. The server computer system may deploy the smart protocol to the particular blockchain platform.
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04W 28/00 - Gestion du trafic du réseau; Gestion des ressources du réseau
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
Techniques are disclosed relating to determining identity information of a user associated with a blockchain address. An application of a first user can receive information indicative of a blockchain address of a second user. This information either includes or is usable to retrieve a certificate of the second user, which is signed by a private key of a certificate authority (CA), and which includes identity information of the second user. The application of the first user can verify the certificate using a public key of the CA. The application of the first user can then cause identity information of the second user to be included in a user interface presented to the first user. This information allows the first user to have more information about the second user before commencing an irreversible blockchain transaction with that user.
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
17.
INTERFACE WIDGET TOOL FOR AUTOMATIC QR CODE GENERATION AND DISPLAY WITHOUT APPLICATION LAUNCHING
There are provided systems and methods for an interface widget tool for automatic QR code generation and display without application launching. A user may engage in a transaction with another user, such as a purchase of goods, services, or other items a merchant at a merchant location using machine-readable codes. A machine-readable code may be provided via a mobile device of a user. In order to provide faster and more efficient code generation, an interface widget or other tool may be provided, which, on selection, may execute API calls to a server of a transaction processor. The transaction processor may generate a code without requiring the user to go through a code generation and processing flow in a corresponding application. The code may be limited in validity and may be presented via the widget. Once scanned, the code may provide encoded data for a financial instrument.
G06F 8/76 - Adaptation d’un code de programme pour fonctionner dans un environnement différent; Portage
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/42 - Confirmation, p.ex. contrôle ou autorisation de paiement par le débiteur légal
H04L 67/133 - Protocoles pour les appels de procédure à distance [RPC]
18.
ON-DEVICE DATA PRIVACY OPERATIONS TO PREVENT DATA SHARING AT USER LOCATIONS
There are provided systems and methods for on-device data privacy operations to prevent data sharing at user locations. A service provider, such as a merchant location of a merchant and/or associated online transaction processor, may provide additional services for to users via user data that may be tracked or stored of the user. However, the user may not want to share certain data with the merchant or other backend processor for privacy concerns. Thus, on-device data privacy operations may be used to detect when a user is at a location that has a corresponding privacy setting to hide or abstract user data for the location. The privacy setting may designate data to prevent from sharing when the user uses their device with devices associated with the location. Abstracted data associated with recommendations or actions to provide the user may be generated and provided to a merchant for the location.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
H04W 4/80 - Services utilisant la communication de courte portée, p.ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
H04L 12/66 - Dispositions pour la connexion entre des réseaux ayant différents types de systèmes de commutation, p.ex. passerelles
19.
DECENTRALIZED IDENTITY ON BLOCKCHAIN FOR A MULTI-SIDED NETWORK
Techniques are disclosed relating to facilitating secure communication of private user data between different entities via an intermediary platform. In some embodiments, a computer system executes an identity service to receive via an issuer service of the identity service, credentials of a holder entity. The identity service stores the credentials in a wallet of the holder. The identity service receives, via a verifier service of the identity service, a verification request for the holder based on the credentials. In response to the holder approving the verification request, the identity service evaluates, via a blockchain using at least a decentralized identifier (DID) of an issuer entity utilizing the issuer service, the verification request, including verifying portions of user data included in the credentials. The identity service sends, via the verifier service, a response to the verification request that does not include an entirety of the credentials stored in the holder wallet.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
G06F 21/33 - Authentification de l’utilisateur par certificats
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
20.
INTERFACE MOVEMENT MODELLING FOR ENTITY CLASSIFICATION
Techniques are disclosed relating to determining whether to authorize a requested action based on whether an entity is an automated computer. In some embodiments, a computer system tracks, at a user interface of a computing device, a sequence of pointer movements. The computer system maps, based on coordinate locations of pointer movements in the sequence, respective movements in the sequence to a plurality of functional areas. Based on the mapping, the computer system generates a movement graph and determines, based on the movement graph, whether an entity associated with the sequence of pointer movements is an automated computer. In response to receiving a request to authorize an action at the computing device, the computer system generates, based on the determining, an authorization decision for the action and transmits the authorization decision to the computing device. Determining whether the entity is an automated computer may advantageously prevent fraudulent activity.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/50 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
Methods and systems are presented for tracking activities that occur off of a first layer blockchain in in a second layer network built on the first layer blockchain. In one embodiment, a computer system determines that a transfer of cryptocurrency from a first node to a second node has transpired in the second layer network based on querying channel capacities in the second layer network. The computer system determines a first public address for the first node based on information associated with a first channel that connects the computer system and the first node in the second layer network, and determines a second public address for the second node based on information associated with a second channel that connects the computer system and the second node in the second layer network. The first public address and the second public address are used to monitor activity in the first layer blockchain.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
G06F 21/33 - Authentification de l’utilisateur par certificats
22.
EXTRACTING WEBPAGE FEATURES USING CODED DATA PACKAGES FOR PAGE HEURISTICS
There are provided systems and methods for extracting webpage features using coded data packages for page heuristics. A service provider server may provide website agnostic tools that account for differences in webpage layouts. This may be done using coded data packages designed to consider webpage heuristics of different webpages. These data packages include entries that have a term, a weight, and an optional scope for searching or filtering webpage elements in webpage document code for webpages. Using multiple entries in a data package, a decision may be returned of whether a webpage includes a certain feature, data, or element, as well as data for the element. The identified feature may be used for data extraction and/or determination, which may allow one or more applications and/or browser extensions to provide services across multiple different websites without specifically formulating the data packages for certain website styles.
Quantum computers with a limited number of input qubits are used to perform machine learning processes having a far greater number of trainable features. A list of features of a field are divided into a plurality of feature groups. Each of the feature groups includes a respective group of some, but not all, of the features. A first machine learning process is performed to train a first instance of a quantum computer model, where the feature groups are used as inputs. Based on the first machine learning process being performed, a subset of the feature groups is selected for a second machine learning process. Thereafter, the second machine learning process is performed to train one or more second instances of the quantum computer model. The individual features of the selected subset of the feature groups are used as inputs for the second instances of the quantum computer model.
Methods and systems are presented for collectively storing, managing, and analyzing data associated with different data sources. A data management system defines an enterprise data model schema based on different data model schemas associated with the different data sources. The data management system generates, for each data source, an enterprise data model instance based on the enterprise data model schema. Data is ingested from the different data sources, and then transformed and stored in a corresponding enterprise data model instance based on a mapping between a corresponding data model schema and the enterprise data model schema. Upon ingesting the data from the data sources, one or more consolidated data views are generated that combine at least portions of data from different enterprise data model instances. The data arranged according to the one or more consolidated data views is presented on a device and/or further analyzed to produce an analysis outcome.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
Various techniques for determining risk assessment predictions and decisions are disclosed. Certain disclosed techniques include the implementation of neural network models in determining predictions of risk for an operation based on an input dataset. The disclosed techniques include training the neural network models to compensate for deprecation of variables from the input dataset. The neural network models may be trained to be robust in view of deprecated variables by dropping variables from the input space during training of the neural network models.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
Various techniques for determining risk assessment predictions and decisions are disclosed. Certain disclosed techniques include the implementation of decision-tree based models in determining predictions of risk for an operation based on an input dataset. The disclosed techniques include pruning decision trees to compensate for deprecation of variables from the input dataset. Decision trees may be pruned at nodes associated with the deprecated variables to inhibit the decision trees from breaking down during operation on an input dataset having deprecated variables.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
Systems and methods for real-time electronic service processing adjustments are disclosed. In an embodiment, a computer system may determine that a user account activity has triggered an assessment checkpoint from a plurality of assessment checkpoints in a life cycle of a user account. The computer system may retrieve data from the assessment checkpoint and update a lifetime score for the user account based on the retrieved data. The computer system may update the lifetime score by weighting the retrieved data as one or more features in a linear-weighted lifetime score model, for the life cycle. The computer system may adjust a response threshold for the assessment checkpoint based on the updated lifetime score.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
The present disclosure provides techniques for efficient blockchain transaction processing. In one embodiment, a computer system broadcasts a first transaction to a blockchain network for addition to a block in a blockchain. The computer system may broadcast a second transaction to the blockchain network for addition to the block in the blockchain, where the second transaction descends from the first transaction and includes a placeholder fee. The computer system monitors and determines that the first transaction has not been confirmed to the block in the blockchain for a duration of time (e.g., stuck in the mempool). In response to determining that the first transaction is stuck, the computer system may transmit a request to replace the placeholder fee with a transaction fee that is sufficiently high to cause the first transaction and the second transaction to be confirmed to a block in the blockchain, thereby unsticking the first transaction.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
Novel technical ways of facilitating secured execution of blockchain transactions are presented, the system comprising: generating and training one or more models using real-world block-chain transaction data; receiving a request to perform a simulation of one or more transactions on a first blockchain of the one or more blockchains; identifying a first model of the one or more models that corresponds to the first blockchain, determining a transactional stress level for the simulation, determining a number of nodes for the simulation; and executing, using the first model, the simulation based on the request to predict a result of the one or more transactions if they were executed on the first blockchain.
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p.ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
G06N 7/02 - Agencements informatiques fondés sur des modèles mathématiques spécifiques utilisant la logique floue
Techniques are disclosed for automatically generating and updating a control group. In disclosed techniques, a server computer system trains, using a plurality of transactions, a machine learning model. During training the machine learning model learns a feature distribution of both a current set of control group (CG) transactions and a current set of non-control group (non-CG) transactions included in the plurality of transactions. The system inputs the current set of CG transactions into the trained machine learning model. Based on the output of the trained machine learning model for the current set of CG transactions, the system modifies the current set of CG transactions to generate an updated set of CG transactions. Based on the updated set of CG transactions, the server performs one or more preventative measures for a transaction processing system. The disclosed techniques may advantageously improve the accuracy e.g., of a transaction processing system.
Methods and systems are presented for providing a framework for facilitating multi-party computation within a sharding environment. After a blockchain is divided into multiple shard chains, a multi-party computation system obtains attributes associated with a first shard chain. The attributes may represent characteristics of the first shard chain, characteristics of transactions recorded in the first shard chain, and characteristics of the computer nodes configured to manage the first shard chain. Based on the attributes, the multi-party computation system determines a multi-party computation scheme that specifies a minimum threshold number of nodes required to participate in a transaction validation process and at least one required node required to participate in the transaction validation process for the first shard chain. The multi-party computation system configures the computer nodes configured to manage the first shard chain to perform the transaction validation process according to the multi-party computation scheme.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
H04L 41/06 - Gestion des fautes, des événements, des alarmes ou des notifications
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p.ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
Novel technical ways of analyzing a blockchain system using machine learning are presented. In various embodiments, A system can deploy, by a first entity, a policy smart contract on a blockchain to analyze a first smart contract deployed by a second entity, wherein the policy smart contract is governed by a set of rules, wherein the policy smart contract performs a first assessment that includes analyzing a set of functionalities of the first smart contract and detects a set of vulnerabilities associated with the first smart contract based on the set of rules. The system can determine at a first time a risk score corresponding to the first smart contract based on the analyzing and the detecting. In response to determining that the risk score is above a threshold score, the system can restrict users of a first platform corresponding to the first entity from accessing the first smart contract.
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 12/22 - Dispositions pour interdire la prise de données sans autorisation dans un canal de transmission de données
Systems/techniques for facilitating context-enhanced category classification are provided. In various embodiments, a system can access a first textual description of a product or service. In various aspects, the system can identify, via execution of named entity recognition, one or more keywords in the first textual description. In various instances, the system can access, from a set of queryable databases, one or more second textual descriptions that respectively correspond to the one or more keywords. In various cases, the system can generate, via execution of word embedding, a first numerical representation of the first textual description and one or more second numerical representations of the one or more second textual descriptions. In various aspects, the system can identify, via execution of a machine learning classifier, a category label for the product or service, based on the first numerical representation and the one or more second numerical representations.
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
Novel technical ways of facilitating secured execution of blockchain transactions are presented. In various embodiments, A system, comprising a processor and a non-transitory computer-readable medium having stored thereon computer-executable instructions that are executable by the processor to cause the processor to perform operations comprising: receiving a set of biometric identifiers; in response to receiving the set of biometric identifiers, validating the set of biometric identifiers; in response to validating the set of biometric identifiers, encoding, using a synthesizer, the set of biometric identifiers with a digital-key to generate a multi-factor signature; and causing a block-chain transaction to be executed using the multifactor signature.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
35.
IMPLEMENTING A CRYPTOGRAPHY AGENT AND A SECURE HARDWARE-BASED ENCLAVE TO PREVENT COMPUTER HACKING OF CLIENT APPLICATIONS
A cryptography agent is implemented to serve as an intermediary for a client application executing on an unsecured portion of a machine to bring greater hardware-based security to the client application. The cryptography agent does so by generating a public/private key pair for the client application and sealing the key pair inside an enclave that resides on a secured portion of the machine. The cryptography agent fetches confidential information for the client application from a secure server, where the confidential information is encrypted using the public key. The cryptography agent seals the confidential information using seal keys that are directly fused into hardware of the machine on which the enclave resides, which prevents the client application from accessing the confidential information in plaintext form. The client application sends commands to the cryptography agent, which performs operations within the enclave according to the commands once the client application is validated.
G06F 21/53 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p.ex. "boîte à sable" ou machine virtuelle sécurisée
G06F 21/10 - Protection de programmes ou contenus distribués, p.ex. vente ou concession de licence de matériel soumis à droit de reproduction
G06F 21/33 - Authentification de l’utilisateur par certificats
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
36.
COMPONENT-BASED RISK EVALUATION TECHNIQUES USING PROCESSING FLOW SIGNATURES
Techniques are disclosed relating to component-based risk evaluation using flow signature values. In various embodiments, the disclosed techniques include a server system providing a service usable to provide various computing operations for requesting users, where the server system includes various components with associated component identifier values. In various embodiments, different sequences of the components are usable to perform different ones of the various computing operations. In response to a request from a client device, the server system may perform a requested computing operation via a processing flow that utilizes a particular sequence of components. In various embodiments, the server system generates a particular flow signature value for that particular processing flow, including by generating a flow identifier value by combining component identifier values for the particular sequence of components.
Computer software architectures are disclosed that use improved machine learning techniques for computer data security, data science, and data privacy protection. Computer operations are improved by more efficiently and effectively processing relevant data, such as web browsing history data. Web browsing data that are representative of web browsing history based on activity associated with a web browser application determined. Using a base model and based on the web browsing data, federated machine learning applied to past web browsing data representative of past web browsing history associated with other web browser applications other than the web browser application can be used to generate an updated targeted model.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
G06F 3/00 - Dispositions d'entrée pour le transfert de données destinées à être traitées sous une forme maniable par le calculateur; Dispositions de sortie pour le transfert de données de l'unité de traitement à l'unité de sortie, p.ex. dispositions d'interface
Blockchain latency is improved by unclogging a mempool, which frees up electronic memory and reduces CPU usage and network bandwidth. Mining data of one or more initial blocks of a blockchain is accessed. The mining data reveals, for each miner, the time delay between individual transactions mined by that miner. A subset of miners is then determined to have lower time delays than miners not in the subset. Thereafter, a different random number is generated for each new block of the blockchain system to be mined. Based on a comparison of this random number and a predefined threshold, either an exploitation phase or an exploration phase is entered for the mining of each new block. In the exploitation phase, mining tasks are assigned only to the subset of the miners. In the exploration phase, mining tasks are assigned to both miners within the subset and miners not in the subset.
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06F 21/64 - Protection de l’intégrité des données, p.ex. par sommes de contrôle, certificats ou signatures
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate video/animated quick response (QR) codes are provided. A processor can decompose the QR code into a static fragment and a plurality of dynamic fragments. In various cases, the static fragment can be a portion of the QR code that contains sufficient information to facilitate an online transaction, whereas the plurality of dynamic fragments can be a plurality of portions of the QR code that collectively contain sufficient information to facilitate an offline transaction, in various instances, the processor can sequentially render a plurality of frames on an electronic display, where each frame depicts the static fragment and a corresponding one of the plurality of dynamic fragments.
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p.ex. forme, nature, code
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
Techniques are disclosed for storing and retrieving large amounts of data in a non-relational database using sort keys. A server computer system may receive a request for raw data specifying a start timestamp and an end timestamp. The server determines a start key and an end key for performing a query on a distributed non-relational database storing key-value pairs, where the determining is based on the start timestamp and the end timestamp. The server may compare the start key and the end key to a sort key included in row keys of key-value pairs stored in the non-relational database. Based on the comparing, the server retrieves one or more rows of raw data from the non-relational database. The server generates a graphical representation of the one or more rows of raw data retrieved from the non-relational database. The disclosed techniques may advantageously improve the efficiency of a database management system.
Methods and systems are presented for providing a framework for facilitating eventbased triggers of auxiliary cryptocurrency transactions via a Layer 2 cryptocurrency computer network. A transaction system detects a triggering event associated with a first digital wallet. Based on the detected event, the transaction system determines an auxiliary cryptocurrency transaction for the first digital wallet. Without recording the auxiliary cryptocurrency transaction in a public ledger associated with the cryptocurrency, the transaction system conducts the auxiliary cryptocurrency transaction via the Layer 2 cryptocurrency computer network via one or more payment channels established by computer nodes in the Layer 2 cryptocurrency computer network.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
42.
EXHAUSTIVE LEARNING TECHNIQUES FOR MACHINE LEARNING ALGORITHMS
Techniques are disclosed relating to exhaustive learning techniques for machine learning algorithms. The disclosed techniques include performing an iterative machine learning operation that includes training a first version of a machine learning model (e.g., a decision tree model) based on a current version of a training dataset, where the first version of the machine learning model includes a plurality of decision branches, identifying a first subset of data samples that satisfy evaluation criteria included in a first one of the plurality of decision branches, and removing this first subset of data samples to generate an updated version of the training dataset. The disclosed techniques include repeating the iterative machine learning operation using the updated version of the training dataset to produce a final trained version of the machine learning model.
There are provided systems and methods for sentence level dialogue summaries using unsupervised machine learning for keyword selection and scoring. A service provider, such as an electronic transaction processor for digital transactions, may provide live chat service channels for assistance through live agents and chatbot services. When interacting with these channels over a period of time, a user may create a dialogue with multiple different live agents and/or chatbots. These chat sessions may be asynchronous but have important and relevant information for future live agents to review. Thus, the service provider may provide a dialogue summarizer, which may summarize a dialogue automatically to a number of most relevant sentences. This may be done using an unsupervised machine learning system that utilizes different machine learning algorithms to select and rank keywords within the sentences. The sentences are then scored and highest scored sentences are output as a summary.
A computing device accesses a session log that includes a recording of user interactions of a user during a session with an application instance in a computing environment. The computing device cleanses the session log to remove a portion of the content included in the session log to generate a cleansed session log and converts the cleansed session log into a session vector representation using a finite dictionary built from a plurality of session logs associated with a plurality of users that have interacted with the computing environment. The computing device generates a user model for the user using the session vector representation and a plurality of other session vector representations associated with the user. The model may be used to perform management and security operations in the computing environment.
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
G06F 16/9536 - Personnalisation de la recherche basée sur le filtrage social ou collaboratif
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p.ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
Techniques are disclosed in which a computer system receives a transaction request and uses a federated machine learning model to analyze the transaction request. A server computer system may generate a federated machine learning model and distribute portions of the federated machine learning models to other components of the computer system including a user device and/or edge servers. In various embodiments, various components of the computer system apply transaction request evaluation factors to the portions of the federated machine learning model to generate scores. The server computer system uses the scores to determine a response to the transaction request.
There are provided systems and methods for edge computing storage nodes based on location and activities for user data separate from cloud computing environments. A service provider, such as an online transaction processor, may provide additional services for to users via edge computing systems and edge computing storage nodes. The service may be for data that may be predictively loaded to the edge computing storage node for a particular location, where the edge computing storage node may reside more locally to the location on a network so that data may be served quicker and with less network resource consumption than providing data from a remote cloud computing storage. The data may be predicted to be needed or useful to the user at the location using a user profile for the user, monitored user activities, and/or one or more machine learning models that predict user behaviors at the location.
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p.ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
Techniques are disclosed relating to methods that include preprocessing, by a computer system, records of a database to create one or more token sets for a given record. The created token sets may correspond to ones of a plurality of search string functions, and may include token sets that include a plurality of possible substrings located within data strings of a corresponding database record. The methods may further include receiving a query for a search of the database. The query may include at least one of the plurality of search string functions. The method may also include performing the search by traversing, using at least a portion of the records, at least one token set corresponding to the included search string functions, as well as returning results for the search based on the query and the traversing.
Systems and/or techniques for facilitating image forgery detection via pixel-metadata consistency analysis are provided. The system can receive an electronic image from a client device. The system can obtain a pixel vector and/or an image metadata vector that correspond to the electronic image. The system can determine whether the electronic image is authentic or forged, based on analyzing the pixel vector and the image metadata vector via at least one machine learning model.
Techniques are disclosed relating to the execution of machine learning models on client devices, particularly in the context of transaction risk evaluation. This reduces computational burden on server systems. In various embodiments, a server system may receive, from a client device, a request to perform a first operation and select a first machine learning model, from a set of machine learning models, to send to the client device. In some embodiments the first machine learning model is executable, by the client device, to generate model output data for the first operation based on one or more encrypted input data values that are encrypted with a cryptographic key inaccessible to the client device. The server system may send the first machine learning model to the client device and then receive, from the client device, a response message that indicates whether the first operation is authorized based on the model output data.
G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
50.
DATA SHARING IN GEOGRAPHICALLY PARTITIONED NETWORKS
Techniques are disclosed for the sharing and transferring of user data in online network systems operating in multiple jurisdictions. The different jurisdictions may be, for example, different geo-partitions in an online network system. Various techniques are disclosed for providing cross-partition operational functionalities (e.g., cross-geo transactions) between geo-partitioned server systems through the sharing and transferring of data between the geo-partitions. The geo-partitions may have established permissions for data that can be shared between the geo-partitions. A server system in one geo-partition may generate an auxiliary account from a subset of data shared across the geo-partitions that complies with the data permissions. Complying with the established data permissions may inhibit overlapping between the different laws or regulations of the geo-partitions.
Systems and techniques for facilitating implicit curriculum learning are provided. These allow for improved machine learning systems that can automatically execute curriculum learning without drawbacks such as pre-sorting data into different epochs which may have varying degrees of difficulty (e.g. easiest first, then harder epochs). Applicant's techniques can be executed more efficiently by automatically iterating over a data set, which need not be manually separated into different epochs. Thus, a system can access a neural network and a set of labeled data candidates. In various aspects, the system can perform a plurality of training epochs on the neural network based on the set of labeled data candidates. In various instances, the system can iteratively update the set of labeled data candidates as the plurality of training epochs are performed, by removing, after each training epoch, a dropout percentage of those labeled data candidates which the neural network correctly classified during the training epoch.
Techniques are disclosed in which a computer system receives, from a plurality of user computing devices, a plurality of device-trained models and obfuscated sets of user data stored at the plurality of user computing devices, where the device-trained models are trained at respective ones of the plurality of user computing devices using respective sets of user data prior to obfuscation. In some embodiments, the server computer system determines similarity scores for the plurality of device-trained models, wherein the similarity scores are determined based on a performance of the device-trained models. In some embodiments, the server computer system identifies, based on the similarity scores, at least one of the plurality of device-trained models as a low-performance model. In some embodiments, the server computer system transmits, to the user computing device corresponding to the low-performance model, an updated model.
Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate adaptable QR codes to launch customized experiences are provided. In various embodiments, a system can receive, from a client device, a quick response (QR) code, a client identifier, and location data associated with the client device. In various aspects, the system can identify, from a plurality of merchants, a first merchant that corresponds to the QR code, based on identifying that the first merchant corresponds to the location data. In various instances, the system can identify, from a plurality of client profiles, a first client profile that corresponds to the client identifier. In various cases, the system can identify a digital content based on the first merchant and the first client profile. In various aspects, the system can cause the digital content to be provided to the client device.
G06F 16/9035 - Filtrage basé sur des données supplémentaires, p.ex. sur des profils d'utilisateurs ou de groupes
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p.ex. forme, nature, code
54.
DYNAMIC NODE INSERTION OF SECONDARY SERVICES FOR HIGH-AVAILABILITY DURING MAIN DECISION FAILURE AT RUNTIME
There are provided systems and methods for dynamic node insertion of secondary services for high-availability during main decision failure at runtime. A service provider, such as an electronic transaction processor for digital transactions, may utilize different decision services that implement rules and/or artificial intelligence models for decision-making of data including data in production computing environment. A main decision service may normally be used for data processing and decision-making. However, at certain times, the main decision service may fail, such as if a data processing node fails to process data or times out while processing a data processing request, such as during electronic transaction processing. During this runtime, a dynamic injection processor may dynamically inject a node that performs a call to a secondary service to process the data on behalf of the node and/or main decision service so that a response is provided to the data processing request.
H04L 41/5009 - Détermination des paramètres de rendement du niveau de service ou violations des contrats de niveau de service, p.ex. violations du temps de réponse convenu ou du temps moyen entre l’échec [MTBF]
H04L 65/80 - Dispositions, protocoles ou services dans les réseaux de communication de paquets de données pour prendre en charge les applications en temps réel en répondant à la qualité des services [QoS]
G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
H04L 67/1004 - Sélection du serveur pour la répartition de charge
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p.ex. la mémoire disponible ou la charge de travail
H04L 67/1012 - Sélection du serveur pour la répartition de charge basée sur la conformité des exigences ou des conditions avec les ressources de serveur disponibles
H04L 67/1025 - Adaptation dynamique des critères sur lesquels repose la sélection du serveur
A token issuance system receives a first purchase request for at least one of a good or a service from a merchant at a merchant location. The system generates a payment token based on the purchase request such that the payment token is associated with a proximity condition. The system then determines that a location of a user device that is associated with the purchase request satisfies the proximity condition. In response to the determining that the location of the user device that is associated with the purchase request satisfies the proximity condition, the system provides the payment token to the merchant.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
56.
SYSTEMS AND METHODS FOR PRESENTING AND ANALYZING TRANSACTION FLOWS USING TUBE MAP FORMAT
Methods and systems are presented for analyzing transactions conducted through user accounts with an online service provider based on a tube map structure. A transaction analysis system identifies a seed user account based on a set of risk factors, and generates a tube map based on a transaction flow originated from the seed user account. The tube map represents the transactions within the transaction flow using a multi-tier structure. The transaction analysis system disposes nodes representing different user accounts in different tiers of the tube map to illustrate when the transactions occur within the transaction flow. The transaction analysis system analyzes the transactions using the tube map to identify user accounts that likely involve in suspicious activities. One or more actions can be performed on the user accounts to improve the security of the online service provider.
Systems and methods for smart cloud caching using edge computing and real-time customer journey insights are disclosed. In one embodiment, a system identifies a trend in communications received by a first edge cloud server, wherein each communication corresponds to a customer journey comprising user action steps performed in a client application. The system determines which user action steps cause API invocations to non-edge cloud servers and generates a sequence of API invocations in an order associated with the sequence of user action steps of the customer journey. The sequence of API invocations may be chained and/or bundled and stored in a cache for replication at edge cloud servers. The system may determine that the trend is pervasive in a geographical location based on satisfaction of a criteria, and replicate the cached sequence of API invocations at a cache of a second edge cloud server that services the geographical location.
The present disclosure relates to machine learning related reject inference techniques that utilize attributes of unlabeled data samples. Specifically, the present techniques allow for machine learning based classification of data that might otherwise not be classifiable using another type of classification algorithm. This can improve computer efficiency and security. A computer system may process unlabeled data samples, using a classification model, to generate a plurality of model scores. The computer system may then classify a first unlabeled data sample into one of two categories. This classifying can include selecting a set of unlabeled data samples, from the plurality of unlabeled data samples, that have model scores exceeding a threshold, identifying a plurality of attributes of the set of unlabeled data samples that contributed to the model scores exceeding the particular threshold, and, based on the plurality of attributes, generating a new labeled data sample belonging to a particular category.
Systems, methods, and computer program products are directed to machine learning techniques that use a separate embedding layer. This can allow for continuous monitoring of a processing system based on events that are continuously generated. Various events may have corresponding feature data associated with at least one action relating to a processing system. Embedding vectors that correspond to the features are retrieved from an embedding layer that is hosted on a separate physical device or a separate computer system from a computer that hosts the machine learning system. The embedding vectors are processed though the machine learning model, which may then make a determination (e.g. whether or not a particular user action should be allowed). Generic embedding vectors additionally enable the use of a single remote embedding layer for multiple different machine learning models, such as event driven data models.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p.ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
60.
USING AN INTERNAL LEDGER WITH BLOCKCHAIN TRANSACTIONS
Disclosed techniques relate to reducing computations for certain blockchain-related transactions. Software algorithms and architecture allow some transactions to avoid the need for recordation on a blockchain, which can be computationally expensive both for a requesting device and for various nodes on the blockchain. A computer system may receive indications of incoming transactions transferring digital assets to particular user accounts, and in response to requests from user accounts, the computer system facilitates one or more internal transactions between those accounts. In response to a request from a particular internal user account, the computer system may perform an outgoing transaction that transfers one or more digital assets to an external user account from one or more internal user accounts. The incoming transactions and outgoing transaction are recorded on the blockchain, but the internal transactions are recorded on an internal ledger rather than the blockchain, saving computational power and improving computer operations.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/38 - Architectures, schémas ou protocoles de paiement - leurs détails
Systems and/or techniques for facilitating image forgery detection via headpose estimation are provided. A system (102) can receive a document (104) from a client device. The system (102) can identify, by executing a first trained machine learning model (202), an object that is depicted in the document (104). The system (102) can determine, by executing a second trained machine learning model (402), a pose of the object. The system (102) can determine, by executing a third trained machine learning model (602), whether the document (104) is authentic or forged based on the pose of the object. The system (102) can, in response to determining that the document (104) is forged, transmit an unsuccessful validation message to the client device.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
62.
ADVERSE FEATURES NEUTRALIZATION IN MACHINE LEARNING
Methods and systems are presented for identifying and neutralizing adverse input features that negatively impact accuracy of a machine learning model. A machine learning model is configured to produce an output based on parameter values corresponding to input features. Each input feature is evaluated with respect to its impact on producing a correct output by the machine learning model. One or more adverse input features that have a negative impact on accuracy of the machine learning model are determined. When a request to assess a data is received, input values associated with the data and corresponding to the set of input features are obtained. One or more input values corresponding to the adverse input features are identified. The one or more input values are altered, and the altered input values along with other unaltered input values are used to generate a more accurate output by the machine learning model.
Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.
Methods and systems described herein may implement non-fungible tokens that implement a programmable grammar-based syntax in a variety of environments. In an embodiment, a first non-fungible token that implements a programmable grammar-based syntax standard and includes a first updatable programmable section is generated. The first non-fungible token includes at least one of first executable instructions or first data, and a first portion of the at least one of the first executable instructions or the first data is stored, according to the grammar-based syntax standard, in the first updatable programmable section. The first non-fungible token may then be stored at a first blockchain address on a blockchain, and the first portion of the at least one of the first executable instructions or the first data in the first updatable programmable section of the first non-fungible token is subsequently changed to at least one of second executable instructions or second data.
Techniques are disclosed relating to a graphical user interface (GUI) that is operable to depict data lineage information in levels. In some embodiments, data lineage information may specify a directed graph that is indicative of a data lineage associated with a plurality of data elements. For example, in the data lineage information, the plurality of data elements may be represented as a corresponding plurality of nodes and, in the directed graph, the plurality of nodes may be connected by edges in a manner that is indicative of the data lineage relationships between the plurality of data elements. In various embodiments, the disclosed techniques may generate a data lineage GUI that, for a selected data element of the plurality of elements, is usable to navigate different levels of the data lineage in an upstream and downstream direction relative to a particular level of the selected data element.
Methods and systems are presented for dynamically modifying electronic content presented on a user device by third-party content providers based on goals associated with one or more entities. A content modification system may receive inputs related to goals for a user. The content modification system may synthesize the goals associated with the user. When the user uses a user device to request content from a third-party server, the content modification system may obtain the content and extract items included within the content. The content modification system may modify the content based on the synthesized goals, such as re-arranging the items, highlighting some of the items, or adding and/or removing items. The content modification system may cause the user device to present the modified content.
Techniques are discussed for grouping access requests made to a computer system using a log of access requests that includes a plurality of log entries of that include (a) a plurality of traffic indicators of the corresponding access request and/or (b) a plurality of identity indicators of a respective remote computer system that made the corresponding access request. The plurality of log entries is analyzed using a plurality of network analysis rules that are useable to group log entries according to traffic and/or identity indicators. Based on the analyzing, a plurality of groups of log entries are identified, and each group of log entries is assigned a corresponding common actor identifier (common actor ID). The determination of whether to grant a particular access request uses one or more assigned common actor IDs.
Methods and systems are presented for providing comprehensive payment transaction services through a digital wallet. The digital wallet enables a user to conduct an electronic transaction with a merchant or another user. In one aspect, the digital wallet may modify a payment arrangement of the electronic transaction. For example, the digital wallet may determine a first payment arrangement that specifies one or more financial instruments and a payment deferral time period for the electronic transaction. Subsequent to processing the electronic transaction, the digital wallet may determine a different, second payment arrangement for the electronic transaction. The digital wallet may modify the electronic transaction based on the second payment arrangement without canceling the electronic transaction. In another aspect, the digital wallet may manage rewards by dynamically withholding rewards, releasing the rewards, and/or distributing at least portions of the rewards to different users.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/06 - Circuits privés de paiement, p.ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
Tracking and clawing back unspent transaction output (UTXO) tokens mechanism are disclosed for distributed ledger technology-based networks (DLTNs) operating a UTXO-based token transaction model (which can include blockchain networks). Some embodiments comprise receiving a request to transfer a UTXO token in a DLTN operating a UTXO-based token transaction model. Further, the embodiments can include determining that a clawback list includes the genesis token identifier and barred token identifiers of UTXO tokens barred from being transferred on the DLTN. In addition, the embodiments can include determining whether the clawback list includes any of the ancestral token identifiers of the UTXO token and generating an instruction regulating the transfer of the UTXO token in the DLTN based on the determining whether the clawback list includes any of the ancestral token identifiers. Such techniques improve the security and functionality of DLTNs such as a blockchain network.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/30 - Clé publique, c. à d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
70.
DYNAMIC RECONSTRUCTION OF DECISION TREE STRUCTURES
Techniques are disclosed relating to dynamic construction of decision tree structures. In various embodiments, a server system may receive, from a client device, a request to perform a particular operation via an application hosted by the server system. In some such embodiments, the request (e.g., an API request) may specify data values for one or more parameters. Based on a first parameter specified in the request, the server system may dynamically generate a first decision tree structure for an authorization policy used to determine whether to authorize the particular operation. In some embodiments, the first decision tree structure may include a first plurality of interconnected nodes organized into a first hierarchy having multiple levels, where a highest of the levels includes a first subset of nodes that correspond to the first parameter. Based on this first decision tree structure, the server system may then determine whether to authorize the request.
Techniques for data lifecycle discovery and management are presented. Data lifecycle discovery platform (DLDP) can identify data of users, data type, and language of data stored in data stores (DSs) of entities based on scanning of data from databases. DLDP determines compliance of DLDP and DSs with obligations relating to data protection arising out of jurisdictional laws or agreements. DLDP generates rules to facilitate complying with and enforcing laws and agreements. DLDP can determine, and present to authorized users, risk scores relating to levels of compliance of the DLDP, associated platforms, or entities, risk indicator metrics, or a privacy health index of the organization associated with DLDP. DLDP can manage user rights regarding data, and access to data in DSs and information relating thereto stored in secure data store of DLDP. DLDP can remediate issues involving anomalies indicating non-compliance. DLDP can utilize machine learning to enhance various functions of DLDP.
Methods and systems are presented for providing a framework to integrate independent fragment modules into an integrated user interface. The fragment modules can be simultaneously rendered on a user interface page or sequentially rendered across multiple user interface pages. The fragment modules are configured to interact with a user via the user interface. The interactions with the user may trigger an event. When an event associated with a fragment module occurs, the fragment module is configured to broadcast the event. An orchestrator is configured to monitor events associated with different fragment modules. The orchestrator may include an event handler for performing one or more action in response to an event. The action may include configuring another fragment module to modify a presentation and/or perform a transaction based on the event.
Systems and methods for automatic generation of free-form conversational interfaces are disclosed. In one embodiment, a system receives an input from a user device through a conversational graphical user interface (GUI). An intent of the user may be determined based on the received input. Based on the intent of the user, the system may identify, from a plurality of objects available to the system, one or more objects. Each of the plurality of objects has annotations corresponding to element(s) of the object and function(s) of the object. The function(s) corresponding to the element(s) are executable to perform an action upon corresponding elements. Based on the identified object(s) and the annotations of the identified object(s), the system may generate a dynamic dialogue flow for the conversational GUI, where the dynamic dialogue flow is generated in real-time during a conversational GUI session.
Techniques are disclosed relating to detecting and prevent phishing attacks (such as man-in-the-middle attacks) related to multi-factor authentication (MFA) or two-factor authentication (2FA) processes. A system is described that makes a determination of whether to permit or deny a subsequent authentication step (e.g., a 2FA authentication step) based on a level of trust determined between the computing device making the initial authentication request to a service computer system and the computing device being asked to implement the subsequent authentication step (such as a mobile device). The computing device associated with the subsequent authentication step assesses the trust between the devices and makes the determination of whether to permit or deny the subsequent authentication step. The present techniques enhance computer system security against phishing attacks while maintaining a satisfying user experience for legitimate users.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
Systems/techniques facilitating enhanced, transaction-based QR codes are provided. In various embodiments, a processor can store a plurality of electronic personas, where each electronic persona contains data governing electronic generation of quick response (QR) codes. In various cases, the plurality of electronic personas can respectively correspond to a plurality of privacy levels, such that each electronic persona corresponds to a different/unique privacy level. In various aspects, the processor can, in response to a request to generate a QR code, identify a first electronic persona from the plurality of electronic personas, which can correspond to a first privacy level in the plurality of privacy levels. In various instances, the processor can generate the QR code based on the first electronic persona, such that information embedded within the QR code corresponds to the first privacy level. In various aspects, the processor can render the QR code on an electronic display.
H04L 9/12 - Dispositifs de chiffrement d'émission et de réception synchronisés ou initialisés d'une manière particulière
H04L 9/14 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes
H04L 9/16 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes qui sont changés pendant l'opération
Methods and systems described herein improve blockchain storage operations in a variety of environments. A blockchain compression system may determine that a blockchain compression condition associated with a blockchain having a first plurality of blocks has been satisfied. In response, the system compresses the first plurality of blocks using a first hash tree into a first root hash value and stores the first plurality of blocks in a first database. The blockchain compression system generates a first new era genesis block that includes the first root hash value and a first database address of the first database at which the first plurality of blocks are stored. The blockchain compression system stores the blockchain at one or more nodes in a blockchain network. The blockchain includes the first new era genesis block and any previous new era genesis blocks. This may effectively reduce storage requirements for the blockchain, in various embodiments.
There are provided systems and methods for initiating a device security setting on detection of conditions indicating a fraudulent capture of a machine-readable code. A service provider, such as an electronic transaction processor for digital transactions, may provide in-person or device-to-device data transfers through machine-readable codes, such as to effectuate a payment from one mobile device to another. However, unauthorized devices may be in close enough proximity to also capture the code and impermissibly use the code. Thus, device security settings are used to detect whether fraud may occur in certain settings and implement an operation to hide a valid code. This may include operations to obtain information for the unauthorized device, make the code dynamic, or mask the code in a display. Once a nearby valid scanner is detected, such as through emitted light or sound, the valid code may be displayed.
G06F 21/14 - Protection des logiciels exécutables contre l’analyse de logiciel ou l'ingénierie inverse, p.ex. par masquage
G06F 21/24 - par protection directe des données, p.ex. par étiquetage
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p.ex. lecture de la lumière blanche réfléchie
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p.ex. forme, nature, code
G06Q 20/00 - Architectures, schémas ou protocoles de paiement
78.
MULTI-PHASE TRAINING TECHNIQUES FOR MACHINE LEARNING MODELS USING WEIGHTED TRAINING DATA
A computer system relating to multi-phase training of machine learning models using weighted training data. A computer system may train a machine learning classification model in at least two phases. During an initial training phase, the computer system may train an initial version of the classification model based on a training dataset, applying equal weight to the training samples in the training dataset. The computer system may then generate model scores for the training samples using the initial version of the classification model. Based on these model scores, the computer system may generate, for the training samples, corresponding weighting values. The computer system may then perform a subsequent training phase to generate an updated version of the classification model, where, during this subsequent training phase, at least some of the training samples are weighted using their respective weighting values.
Techniques are disclosed relating to maintaining a high availability (HA) database. In some embodiments, a computer system receives, from a plurality of host computers, a plurality of requests to access data stored in a database implemented using a plurality of clusters. In some embodiments, the computer system responds to the plurality of requests by accessing data stored in an active cluster. The computer system may then determine, based on the responding, health information for ones of the plurality of clusters, wherein the health information is generated based on real-time traffic for the database. In some embodiments, the computer system determines, based on the health information, whether to switch from accessing the active cluster to accessing a backup cluster. In some embodiments, the computer system stores, in respective clusters of the database, a changeover decision generated based on the determining.
H04L 12/24 - Dispositions pour la maintenance ou la gestion
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
80.
AUTOMATED DEVICE DATA RETRIEVAL AND ANALYSIS PLATFORM
There are provided systems and methods for an automated device data retrieval and analysis platform. A service provider server invokes an instance of an application in a remote processing environment using device data associated with the application and sends a control message that prompts the instance to send a request to a web server for a process script that invokes a process executable in the remote processing environment. The service provider server obtains traffic data a behavior of application databased on an interaction between the instance and the web server, and determines features of the application in a native state from the behavior of the application data. The server generates a data profile of the application that indicates the features in the native state and provides the data profile to a remote engine to detect potential malicious activity associated with the application from the detection operation.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
Techniques are disclosed relating to a delayed presentation of authentication challenge for users, such as in the context of a chat session. In various embodiments, a server system receives an indication of a request for service initiated by a user in a chat session within an application executed by a client device. The request for service involves an authentication of the user that is dependent on the authentication being successfully completed within a particular time period after the authentication is initiated. The server system delays the initiation of authentication for the request for service until a readiness condition is satisfied. The readiness condition includes the server system being available to process the request for service, as well as subsequently detecting engagement with the user relating to the request for service. In response to the readiness condition being satisfied, the server system initiates the authentication of the user.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
Systems and techniques for facilitating relay attack prevention for electronic quick response (QR) codes are provided. A system can determine a cardinality and frame rate. System can transmit instruction to a mobile device, which can cause the mobile device to generate interlaced frames having the cardinality. The interlaced frames can respectively correspond to portions of a QR code, wherein different interlaced frames depict different QR code portions. The instruction also can cause the mobile device to sequentially render, at the frame rate, the interlaced frames on the mobile device display, causing one portion from the QR code portions to be depicted on the display at a time. System can transmit another instruction to a point-of-sale (POS) device, causing POS device to reconfigure scanner settings of POS device, and enabling POS device to capture the interlaced frames sequentially rendered on the mobile device display based on the cardinality and frame rate.
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p.ex. lecture de la lumière blanche réfléchie
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p.ex. forme, nature, code
G06Q 20/00 - Architectures, schémas ou protocoles de paiement
G06Q 20/30 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques
83.
TECHNIQUES FOR SINGLE ROUND MULTI-PARTY COMPUTATION FOR DIGITAL SIGNATURES
A system and method for digitally signing data. A method includes generating, by a first device, at least one first secret share based on a secret key chosen by the first device, wherein the first device is offline with respect to a second device; partially signing data by the first device using the at least one secret share, wherein the data is received from the second device without establishing direct communications between the first device and the second device; and sending the partially signed data from the first device to the second device, wherein the second device generates signed data using the partially signed data, wherein the signed data corresponds to a public key generated based on the at least one first secret share and at least one second secret share generated by the second device.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
84.
SYSTEMS AND METHODS FOR CREATING AND DISTRIBUTING BLOCKCHAIN-BACKED REDISTRIBUTABLE ELECTRONIC CONTENT COMPONENTS
Methods and systems for creating and distributing blockchain-backed redistributable electronic content components provide greater computer security and authentication controls. An electronic content component associated with a first entity and a first set of actions is created. The electronic content component is published, and the first set of actions and a block representing the electronic content component are added to a blockchain. A second entity requests use of the electronic content component and a distribution agreement between the first and second entities associated with a second set of actions is created. The second set of actions and a block representing the distribution agreement are added to a blockchain. The electronic content component and distribution agreement are validated based on the blockchain, and custom content including the electronic content component is published. When an end-user accesses the electronic content component, the first and second sets of actions are executed.
G06F 21/10 - Protection de programmes ou contenus distribués, p.ex. vente ou concession de licence de matériel soumis à droit de reproduction
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
Techniques are disclosed relating to a method that includes monitoring, by a sideband processor, a plurality of operating conditions of a computer system using a first set of commands. This first set of commands are sent utilizing a particular command protocol over a particular communication bus. In addition, the sideband processor may be modified to support a second set of commands. The sideband processor may receive data for a particular device in the computer system. The sideband processor may modify a first command of the first set of commands to include a second command of the second set of commands. This second command may include an address associated with the particular device and at least a portion of the data. The sideband processor may then send the modified first command to a controller hub using the particular command protocol over the particular communication bus.
Systems and methods for active application of secondary transaction instrument tokens in transaction processing systems are provided. A transaction processing server receives a transaction request identifying a request to authorize a transaction using a first transaction instrument and a first token processing engine issues the transaction request with a first transactable token associated with the first transaction instrument for use by a first remote entity to authorize the first transaction instrument. The transaction processing server receives a transaction request failed message and actively routes a non-transactable token from the first token processing engine to a second token processing engine. The second token processing engine reissues the transaction request with a second transactable token associated with the second transaction instrument for use by a second remote entity to authorize the second transaction instrument and receives an indication that the transaction completed successfully using the second transactable token.
There are provided systems and methods for a payment information autofill mechanism that links a browser application with a user account such that a payment page at the browser application can be automatically filled based on the link. Specifically, the autofill mechanism establishes a link between a browser application running on a user device and a user account associated with the user that is stored at the server. When the user engages with the browser application to conduct a transaction on a merchant website, an application programming interface (API) call can be made to retrieve user virtual card information for automatically populating the payment data fields at the transaction page.
A POS system includes a base stand having a receiving interface having first electrical contacts. The POS system includes a computing device having a user interface, a docking interface comprising second electrical contacts, wherein the docking interface is configured to removably dock the computing device to the receiving interface such that the first electrical contacts are in contact with second electrical contacts of the computing device. The computing device may further include a card reader configured to receive and read a card inserted into the card reader and a NFC component configured to transmit and receive wireless communications to and from the computing device and a user mobile device. The computing device may further include a scanner configured to scan machine-readable codes. The computing device may be configured to extend or enable various functions of the base stand when the computing device is docked to the base stand.
Methods and systems are presented for facilitating migration of electronic shopping carts between devices. A user generates an electronic shopping cart based on interacting with a merchant website using a first device. In response to receiving a request for transferring the electronic shopping cart, cart data associated with the electronic shopping cart is obtained. The cart data is encoded, using a selected encoding technique, into a code, which can be a phrase, an emoji string, a QR code, or an image of a face that can be transferrable to a second device. The code is presented on the first device. In response to receiving the code from the second device, the electronic shopping cart is re-generated based on the cart data extracted from the code. The electronic shopping cart is made accessible to the user via the second device.
A method is disclosed for storing an arranging data in a database. The method includes a computer system storing, in a database, data indicative of a graph data structure having a plurality of nodes connected by a plurality of edges. The method further includes the computer system determining that a number of edges connected to a first node satisfies a threshold number. In response to the determining, the computer system may store an index in an index row associated with the first node. The index identifies a first row having first and second ranges of values stored in first and second rows, respectively. The values in the first and second rows correspond to edges connected to the first node. The values in the first and second ranges are usable to indicate properties of corresponding ones of the plurality of edges.
Techniques for an ultra-fact software compilation of source code are provided. A compiler receives software code and may divide it into code sections. A map of ordered nodes may be generated, such that each node in the map may include a code section and the order of the nodes indicates an execution order of the software code. Each code section may be compiled into an executable object in parallel and independently from other code sections. A binary executable may be generated by linking executable objects generated from the code sections. The methodology significantly differs from existing source code compilation techniques because conventional compilers build executable sequentially, whereas the embodiments divide the source code into multiple smaller code sections and compile them individually and in parallel. Compiling multiple code sections improves the compilations in order of magnitude from conventional techniques.
Techniques are disclosed relating to methods that include receiving an indication of an access by a user to a web page that includes a beacon, and calculating a readiness score for triggering the beacon. The methods may also include determining, based on the readiness score, whether to perform a client-side or server-side triggering of the beacon. The triggering causes data associated with the access to be transmitted to a third-party computer system.
There are provided systems and methods for a database synchronization system in high security zones using blockchain. A service provider, such as an electronic payment provider, may maintain data stores across different zones that may need to synchronize data across these zones. As such, the subject technology provides for data storage using interplanetary file system (IPFS) technology in compliment with blockchain technology to create a secure, scalable and reliable data synchronization system. The IPFS may be implemented as a data storage layer and the blockchain may be implemented as a transaction management system, where the IPFS address of data files and synchronization points are stored in a distributed ledger. In various aspects, the integration of the IPFS network with the fabric network can enhance IPFS with the fabric network to create a more secure file sharing platform to improve the transfer of data and database synchronization between different zones.
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
G06F 17/00 - TRAITEMENT ÉLECTRIQUE DE DONNÉES NUMÉRIQUES Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
94.
TRAINING RECURRENT NEURAL NETWORK MACHINE LEARNING MODEL WITH BEHAVIORAL DATA
Event data of a first entity is accessed. The first entity has been flagged as having a predefined status. The event data corresponds to a plurality of events involving the first entity that occurred within a predefined first time period. Based on the accessing of the event data, behavioral data of the first entity is generated. The behavioral data is formatted as a data sequence. A machine learning model is trained using the behavioral data of the first entity as training data. Using the trained machine learning model, a determination is made as to whether a second entity has the predefined status.
G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
95.
ARTIFICIAL INTELLIGENCE ORCHESTRATION LAYER TO FACILITATE MIGRATIONS BETWEEN DIFFERENT ARTIFICIAL INTELLIGENCE PLATFORMS
There are provided systems and methods for an artificial intelligence (AI) orchestration layer to facilitate migrations between different AI platforms. A service provider may provide AI portability functions through an orchestration layer that connects different AI services and platforms. The orchestration layer may be used to monitor user interactions with a first AI platform that request AI predictive services and outputs. Using these monitored interactions, the service provider may build and train a simulated AI model that attempts to mirror or replicate the AI model trained for the user on the first AI platform. Thereafter, when the user begins use of a second AI platform that includes the same or similar functionalities to the first AI platform, the service provider may utilize the orchestration layer to assist in training an AI model on the second AI platform based on the previously trained AI model on the first AI platform.
Techniques are disclosed relating to improving machine learning classification using both labeled and unlabeled data, including electronic transactions. A computing system may train a machine learning module using a first set of transactions (of any classifiable data) with label information that indicates designated classifications for those transactions and a second set of transactions without label information. This can allow for improved classification error rates, particularly when additional labeled data may not be present (e.g., if a transaction was disallowed, it may not be later labeled as fraudulent or not). The training process may include generating first error data based on classification results for the first set of transactions, generating second error data based on reconstruction results for both the first and second sets of transactions, and updating the machine learning module based on the first and second error data.
Techniques are discussed for preparing and executing scanning plans for particular types of information, including personally identifiable information. A user indicates one or more datastores to be scanned for the particular type of information. A scanner determines scan objectives for the scanning plan and classifiers for use in scans conducted according to the scanning plan. The scanner estimates scan performance metrics and scan quality metrics. The scanner presents estimated results for the scanning plan based on the selected classifiers, scan objectives, estimate scan performance metrics, and estimated scan quality metrics. The user can modify the set of scan objectives or select between alternative sets of scan objectives. The scanning plan may be performed iteratively and the results of previous scan may be used to adjust classifiers or scan objectives to be used in subsequent scans.
Systems, methods, and computer program products for determining an attack on a neural network. A data sample is received at a first classifier neural network and at a watermark classifier neural network, wherein the first classifier neural network is trained using a first dataset and a watermark dataset. The first classifier neural network determines a classification label for the data sample. A watermark classifier neural network determines a watermark classification label for the data sample. A data sample is determined as an adversarial data sample based on the classification label for the data sample and the watermark classification label for the data sample.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
There are provided systems and methods for a user-controlled session manager to provide remote disabling of session tokens. An online service provider, such as a usercontrolled session manager, may provide service to manage sessions between user's devices and other online service provider platforms, such as login and use sessions that exchange messages and data. The session manager may receive hashed values of session IDs from the service providers hosting the sessions, which may be used to securely identify the sessions without compromising the session IDs to malicious parties. The session manager may provide a functionality to allow the user to view session statuses, as well as change their statuses to indicate that the sessions can be terminated. The session manager may update the status so that when the service provider pings the session manager for the status, the session's status is updated to be inactive.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
G06F 17/30 - Recherche documentaire; Structures de bases de données à cet effet
Techniques are disclosed relating to automatically resolving an error in a user interaction with a user page without the user having to disengage from the user page to resolve the error. A monitoring agent may interface with the user page. The monitoring agent may provide an error signal to an error resolution module in response to detecting an error in the user interaction with the user page. The error resolution module may determine a causal factor for the error based on the error signal and contextual data at the time of the error. A resolution flow may be determined based on the causal factor. The resolution flow may be implemented by the monitoring agent contextually within the user page to resolve the error without the user disengaging from the user page.
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