10477results about "Protocol authorisation" patented technology

The present disclosure relates to systems and methods for facilitating interoperability between blockchain networks to facilitate bridging of non-fungible tokens (NFTs) across chains. In embodiments, a method includes receiving a bridging request at a first bridge smart contract to transfer a source NFT from a first blockchain to a second blockchain. Upon verification, the first bridge smart contract locks the source NFT. An oracle server determines whether a clone NFT associated with the source NFT exists on the second blockchain. If so, the oracle instructs a second bridge smart contract to unlock the clone NFT. If no clone NFT exists, the oracle instructs minting of the clone NFT and assigning ownership of the clone NFT to the user's account on the second blockchain. The clone NFT remains controllable by the user while the source NFT stays locked on the first blockchain, maintaining a one-to-one relationship between the tokens across chains.

A computer system comprises at least one processor; and a memory coupled to the at least one processor and storing processor-executable instructions which, when executed by the at least one processor, configure the at least one processor to create a first set of training data that includes data flagged as fraud and data flagged as not fraud; categorize the first set of training data into a number of first groups; for each first group, calculate at least one metric; compare the at least one metric to a number of first cutoff values; select a first cutoff value that generates a maximum performance output as a first threshold; flag at least one first group that has the at least one metric below the first threshold as risky; and generate fraud rule criteria based on the at least one first group.

A server computer system includes a communications module; at least one processor coupled to the communications module; and a memory coupled to the at least one processor, the memory storing processor-executable instructions which, when executed by the at least one processor, configure the at least one processor to receive, via the communications module, an indication that a cheque clearing process has been initiated for a cheque; obtain an account number and a routing number for the cheque; perform a lookup to identify a payor of the cheque; and send, via the communications module and to a client device associated with the payor of the cheque, a real-time update indicating that the cheque has been submitted for collection.

An example method includes for each training iteration in a series of training iterations: receiving, for a first set of unlabeled metrics data, a set of respective labels associated with an account in a set of accounts. The first set of unlabeled metrics data and a second set of unlabeled metrics data can be processed to generate network inputs representing a respective account in the set of accounts. The network inputs can be processed using a teacher neural network that generates an anomaly prediction output for each network input. A student neural network can be trained to optimize a loss function, which can include minimizing a loss term measuring a difference between the anomaly prediction output and the student network's proposed anomaly prediction output and minimizing a loss term measuring a difference between the proposed anomaly prediction output and the account's associated label.

The disclosed embodiments include computer-implemented systems and processes that generate and provision, in real time, directed digital content based on decomposed structured messaging data. For example, an apparatus may receive a plurality of messages that characterize first data exchanges initiated between a first counterparty and second counterparties during a first temporal interval. Each of the messages includes elements of message data associated with a real-time payment requested from the first counterparty by a corresponding one of the second counterparties. Based on the elements of message data, that apparatus may predict an occurrence of a second exchange of data that involves the first counterparty during a second temporal interval, and may transmit notification data that includes product data characterizing an available product associated with the predicted occurrence of the second data exchange to a device operable by the first counterparty for presentation within a digital interface.

The invention discloses a digital asset secure transaction system and method based on a block chain, and belongs to the cross field of block chain technology and financial science and technology. The system adopts a layered architecture design and comprises an intelligent contract execution layer, a distributed account book storage layer and a cross-chain interaction layer. The transaction method comprises the following steps: generating a digital identity certificate based on asymmetric encryption, and realizing privacy protection through zero-knowledge proof; a secure transaction channel is constructed by adopting a multi-signature mechanism, and sensitive data processing is performed in combination with a trusted execution environment; and designing a dynamic fragmentation strategy to optimize the transaction throughput, and establishing an on-chain and off-chain collaborative verification mechanism. The innovation point is that a double-layer verification model combining a verifiable delay function and a threshold signature is provided, and millisecond-level confirmation is realized while the transaction irreversibility is ensured. The system supports multi-chain asset atomic exchange, and interoperability of different block chain networks is realized through a heterogeneous cross-chain gateway. The scheme has the characteristics of high transaction confirmation speed, high privacy protection level and high system expansibility.

Systems, methods, and computer program products are disclosed for selectively employing a processing mode based on a continuous gesture. Selectively employing a processing mode may include detecting an existence of a mode-selection gesture by an individual. Upon detecting the existence of the mode-selection gesture, a first mode for processing facial micromovements of the individual may be continuously implemented while continuously detecting the mode-selection gesture. Following the continuous detection of the mode-selection gesture, a cessation of the mode-selection gesture may be detected. In response, implementation of the first mode may cease, and implementation of a second mode different from the first mode may be initiated for processing facial micromovements of the individual.

The invention relates to the technical field of data processing, and provides an intelligent risk control method for carbon asset transaction, which is used for solving the problems of data island, response lag, low efficiency, safety risk and the like in traditional carbon transaction. According to the invention, standardized access of a carbon emission permit trading system, a registration system and enterprise internal data is realized by constructing a carbon asset data middle platform, integrating a block chain and an RPA technology, a price fluctuation rate and a quota gap risk are calculated in real time based on Apache Flink, a carbon price trend is predicted through an LSTM + Attention model, and an intelligent contract is triggered to generate a hedging instruction; a three-level risk prevention and control system is constructed by adopting an ABAC model and biological characteristic verification, a quota regulation path is optimized through a graph neural network, automatic performance is driven, strategy self-adaption is realized in combination with PPO reinforcement learning and BERT policy analysis, and the problems of data islands, response lag, low efficiency and security risks in traditional carbon transactions are systematically solved.

This invention introduces a 32-dimensional financial security and risk control system designed to address advanced cyber threats and ensure comprehensive protection for financial platforms. It integrates multi-layered encryption, AI-based dynamic risk control, virtual wormholes, and a hive network architecture to secure data transmission, identity verification, and transaction integrity. The system employs smart contracts and AI models to dynamically adjust risk parameters and execute risk mitigation strategies, providing an adaptive and highly secure financial infrastructure.

A system for receiving and temporarily maintaining a delivery item and dynamically initiating a dispatched logistics operation for a storage receptacle. The storage receptacle has an entrance opening for receiving the delivery item, a temporary storage area for temporarily maintaining the delivery item once deposited with the storage receptacle, and a retrieval door providing selective access to the temporary storage area. The system includes a backend server that maintains a management profile related to the storage receptacle, a bridge node mounted to the storage receptacle, and a wireless accessory sensor node having at least one sensor that monitors for a change in state of the storage receptacle. The wireless accessory sensor node broadcasts an updated advertising signal. The bridge node transmits retrieved event information to the backend server at a reporting time, and the backend server initiates the dispatched logistics operation from comparing the retrieved event information to location information.

In accordance with embodiments of the present disclosure, a method for conducting secure financial transactions uses a model-based reflex agent to ensure real-time authorization, anomaly detection, and risk assessment. The agent receives transaction-related data, maintains an internal state reflecting observed and inferred conditions, and applies condition-action rules to determine appropriate actions, such as authorizing payments, triggering multi-factor authentication, or halting transactions. The agent dynamically updates its internal state based on feedback, adapts to changes using machine learning, and ensures compliance through audit logs. This approach enhances security, minimizes fraud, and provides seamless, adaptive processing for financial transactions in dynamic environments.

An enhanced multi-compartment connected logistics receptacle system includes a storage receptacle, a bridge node, and wireless accessory sensor node with a plurality of sensors. A first subset of the sensors is disposed relative to a first monitored receptacle compartment and a second subset of the sensors is disposed relative to a second monitored receptacle compartment. The plurality of sensors monitor for a change in state of the storage receptacle. The wireless accessory sensor node detects the storage receptacle's state change based upon sensor data and broadcasts a signal with a flag set indicating there is event information available for upload. The bridge node detects the flag set, retrieves the event information available for upload from the wireless accessory sensor node, and transmits the retrieved event information to a backend server to cause the backend server to initiate a dispatched logistics operation related to the storage receptacle.

Systems and techniques for location management are described herein. In an example, a system may include at least one processor and at least one memory with instructions stored thereon that when executed by the processor, cause the processor to obtain data originating from one or more sensors proximate to the location. A trained activity-based detection model may identify an activity at the location and perform a determination of a service to be offered at the location based on the detected activity. The system may then send a message to a user offering the service to the user, and in response to receiving an authorization accepting the service from the user, cause the service to be implemented at the location, which may include classifying the service as a service type, matching the service type to a service provider, and sending a notification to the service provider.

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

The invention relates to the technical field of commercial information communication, and discloses an internet marketing platform risk early warning management method and system, and the method comprises the steps: constructing a multi-level heterogeneous risk relation graph, and mapping multi-source heterogeneous data; constructing a dynamic Bayesian causal network, and extracting a causal relationship; establishing an atlas causal bidirectional mapping model to realize information fusion and enhancement; risk propagation potential energy is evaluated based on the model, and the propagation potential is quantified; according to the method, the problems of inaccurate risk propagation prediction, low intervention efficiency, insufficient adaptive ability and the like of the Internet marketing platform are solved, and technical support is provided for safe operation of the platform.

The invention discloses a power transaction market risk dynamic assessment system, which comprises a multi-modal sensing module used for collecting physical equipment operation data, market transaction data and environmental parameters in real time, and performing space-time alignment processing through edge computing nodes to generate a fusion data stream; the self-adaptive evaluation engine is in data connection with the multi-modal sensing module and is used for analyzing multi-dimensional risk association in the fused data stream; the invention belongs to the technical field of electricity markets, and aims to solve the problems that in the prior art, historical data static analysis is relied on, spatial-temporal scales of multi-source data are not uniform, and data cannot be given in time. The technical effects are that a closed loop is formed through sensor data, a multi-mode sensing module (alignment processing), an adaptive evaluation engine (risk analysis), a digital twin system (simulation strategy) and a dynamic feedback module (optimization system), automatic calibration and learning are realized, and the risk prediction accuracy and the reliability of the scheme are improved.

The invention, which relates to the technical field of payment security, discloses a payment-scene-oriented interaction intention identification and error correction system comprising an input analysis module, an intention simulation module, a dynamic decision module, a biological verification module, an audit evidence storage module, and a cross-scene knowledge migration module. According to the method, multi-modal data such as voice, texts, images and touch tracks are integrated, structured feature vectors are generated through a cross-modal attention network, the problem of incomplete single-modal coverage is solved, cross-modal data consistency verification is achieved based on a unified semantic tag system, and the reliability of input sources is graded by combining equipment fingerprints and geographic positions, so that the reliability of the input sources is improved. A high-risk transaction protection capability is enhanced, a generative adversarial network is utilized to construct a virtual attack sample library, attacks such as tampering with characters similar in shape and AI faking voiceprints are simulated, unknown threats are actively defended through cosine similarity matching, a user historical behavior statistical model is integrated, and known risks such as high-frequency small-amount transfer are passively intercepted. And a closed-loop incremental learning continuous optimization model is supported.

A computer-implemented method is provided for a mobile device to detect, by a camera of the mobile device, a plurality of checks; determine, by a processing unit of the mobile device, that the image of the plurality of checks is of sufficient quality; instruct, by a display of the mobile device, a user to take a photograph of the plurality of checks; crop, by the processing unit, the photograph of the plurality of checks into a plurality of images, wherein each of the plurality of images contains one of the plurality of checks; and transmit, by a transmitter of the mobile device, the plurality of images to a server via a network. The plurality of images may be transmitted individually (i.e., one at time), or alternatively, collectively and in one payload.

Systems, methods, and computer program products are disclosed for establishing nonvocalized communications. Establishing nonvocalized communications may include detecting a directional gesture made by a wearer of a first wearable device configured to determine facial skin micromovements of the wearer, wherein the directional gesture identifies a second device in proximity to the first wearable device. Based on the directional gesture, a wireless communication channel for enabling a nonvocalized communication between the first wearable device and the second device is selected. Thereafter, specific facial skin micromovements of the wearer of the first wearable device are determined. The specific facial skin micromovements indicate words to be communicated in an absence of perceptible vocalization by the wearer of the first wearable device. Then, the words are transmitted via the wireless communication channel from the first wearable device to the second device for presentation via the second device.

A system is adapted to automatically report the trustworthiness of an entity. The system includes a processor and a computer readable medium carrying instructions. The instructions include receiving unstructured data pertaining to an entity from public sources, and receiving structured data pertaining to the entity from at least two databases. The instructions also include merging the structured data and the unstructured data into a single document; splitting the single document into chunks; creating embeddings corresponding to the chunks; and storing the embeddings in a vector store. The instructions also include receiving a natural language user query regarding trustworthiness of the entity; converting the query to a query embedding; based on the query embedding and a similarity calculation, fetching a relevant embedding from the vector store; with a large language model (LLM), generating a query response regarding the trustworthiness of the entity; and communicating the query response to the user.

The invention relates to the technical field of asset transaction risk monitoring, and proposes an asset transaction risk monitoring system based on data analysis, and the system comprises a data obtaining module which is used for obtaining and integrating multi-source heterogeneous data, including but not limited to transaction records, market quotation data, user behavior data, legal contract texts and financial indexes, the data is preprocessed; and the risk assessment module is connected with the data acquisition module through a data transmission technology, and assesses the risk in real time based on a preset rule and a machine learning model. Through timely acquisition and analysis of latest transaction information, market dynamics and user behavior changes, a reinforcement learning technology is utilized, and according to a real-time risk assessment result and a disposal effect, risk monitoring is ensured to be always matched with a market actual condition, so that a financial institution can timely capture a risk signal and take precautionary measures in advance, and the risk monitoring efficiency is improved. And the risk loss is effectively reduced.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

Systems and techniques may generally be used for chatbot-based fraud assistance. An example method may include initiating a chatbot session with a user and receiving a prompt from the user related to suspected suspicious activity in an account. The method may include retrieving, using a Retrieval-Augmented Generation (RAG) component, contextual information from at least one of transaction data and a knowledge base. The method may include evaluating the prompt using a large language fraud model and the retrieved contextual information to determine a response.

The invention provides an anti-fraud method and system based on a complex relation network, and the method comprises the steps: carrying out the preprocessing and association rule mining of multi-source data, constructing a heterogeneous relation network model, carrying out the abnormal behavior detection of real-time data, updating the heterogeneous relation network model based on an abnormal behavior detection result and historical data, and carrying out the recognition of the abnormal behavior. And performing risk quantification, community discovery, abnormal path analysis and related result visualization on the updated heterogeneous relation network model, calculating a fraud risk score of each node through a pre-trained machine learning model based on a related result, and finally generating a service instruction of each node based on the fraud risk score and a preset score interval. By adopting the method, the problems of poor adaptability, high false alarm rate, low gang crime recognition rate and the like of the existing anti-fraud technology can be relieved.

Embodiments are directed to methods and systems that can be used to perform efficient, parallel, privacy-preserving graph analysis. One particular application of embodiments is performing private cycle detection in order to detect anomalous behavior in directional electronic communications. Two (or more) parties can each possess private electronic communication data, which can be used to construct a private directed union graph corresponding to the union of the parties' electronic communication data. This private union graph can be analyzed by a multi-party computation network in order to detect cycles of defined length (e.g., comprising between four and eight communicating participants). These cycles can be used as evidence of anomalous or illicit use of such electronic communications systems.

The invention relates to the technical field of financial information security, in particular to a bank abnormal transaction detection method based on multi-modal data fusion, and the method comprises the following steps: S1, collecting a multi-modal original data set of a bank transaction system in real time; s2, carrying out space-time alignment processing, and generating a data incidence matrix with a unified timestamp; s3, extracting a transaction amount fluctuation rate, an operation behavior dispersion degree and an equipment environment abnormity degree, and generating a fusion feature vector; s4, calculating an energy value change gradient of the fusion feature vector, and generating a dynamic energy distribution map; s5, establishing a cross-modal association rule base for generating a logic contradiction value; and S6, outputting a grading abnormity early warning signal. According to the invention, through multi-modal data fusion and energy field model dynamic analysis, transaction abnormal characteristics are accurately captured and dynamic early warning is realized, so that the detection accuracy and the real-time response capability are remarkably improved, and the security of a bank transaction system is enhanced.

A centrally managed system for tuning a plurality of enhanced node-based logistics receptacles includes a backend server, a first enhanced node-based logistics receptacles, and a second node-based logistics receptacles. The backend server transmits a first setup message to a first bridge node, transmits a second setup message to a second bridge node, receives retrieved first event information from the first bridge node and retrieved second event information from the second bridge node, compares the retrieved first event information with a management profile and compares the retrieved second event information with the management profile, revises the management profile based upon the comparison of the retrieved first event information with the management profile and the comparison of the retrieved second event information with the management profile, and transmits an adjustment message that is based upon the revised management profile to the first bridge node.

An enhanced node-based connected logistics receptacle system includes a storage receptacle, a bridge node, and wireless accessory sensor node with at least one sensor monitoring for a change in state of the storage receptacle. The system's wireless accessory sensor node detects the storage receptacle's state change based upon sensor data, records timestamped information reflecting the detected change, and broadcasts a signal with a flag set indicating there is event information available for upload. The system's bridge node is operative to detect the flag set, retrieve the event information available for upload from the wireless accessory sensor node, and transmit a message related to the retrieved event information to a backend server to cause the backend server to initiate the dispatched logistics operation related to the storage receptacle.

A System for providing Interactive Transaction Frameworks, utilizing biometric authentication and semantic web technologies is disclosed. The system registers users with a unique biometric-based identifier, and employs ontologies, schemas, and knowledge graphs to create a semantic foundation. A Large Language Model integrated with the Knowledge Graph Module enables intelligent processing of Interactive Transaction data. The system composes Interactive Transactions with fields mapped to semantic triples, maintains them in an Interactive Transaction Library, and manages user permissions. A Transaction Publishing Platform facilitates Interactive Transaction distribution and submission-response cycles. The system refines inputs and responses, determining outcomes based on these interactions. The system offers a sophisticated, secure, and adaptable approach to Interactive Transaction management and processing across various domains.

An enhanced connected logistics receptacle system that selectively retrieves and reports event information to a backend server to initiate a dispatched logistics operation related to a delivery item. The system includes a storage receptacle for receiving the delivery item, a bridge node mounted to the storage receptacle, and a wireless accessory sensor node coupled to a plurality of sensors. The wireless accessory sensor node is operative to detect a change in state of the storage receptacle based upon sensor data, record timestamped information reflecting the detected change in state, and broadcast an updated advertising signal having a data available flag set within the updated advertising signal. The bridge node processor is operative to detect the data available flag, selectively retrieve event information from the wireless accessory sensor node, and transmit the retrieved event information to the backend server to cause the backend server to initiate the dispatched logistics operation.