585 results about "Trustworthiness" patented technology

In some implementations, the techniques described herein relate to a method including: parsing, by a processor, a generated text to identify statements included within a generated text; querying, by the processor, a remote data source to identify sources for each statement in the statements; determining, by the processor, trustworthiness values for each statement, a trustworthiness value for a given statement determined by computing trustworthiness labels for each source corresponding to a given statement: generating, by the processor, a label for the generated text based on an aggregated trustworthiness of each of the statements; and displaying, by the processor, the generated text and the label within a user interface displayed to a user.

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 discloses a dynamic optimization updating method of a credible data intelligent detection system, which relates to the technical field of credible data detection, and comprises the following steps: deploying heterogeneous feature acquisition nodes, acquiring data association features, operating behavior fingerprints and setting a dynamic credible evaluation threshold value; constructing a gradient aggregation channel based on differential privacy encryption, performing security fusion, generating a global model optimization vector, and generating an adversarial sample set; carrying out weight distribution, configuring a dynamic update step length, and generating an update instruction set; and activating the adversarial sample generation network, generating an incremental update package, triggering asynchronous hot deployment of the edge computing nodes, reconstructing a model topological structure of the federated incremental learning framework, and generating an update log. The technical problems of poor adaptability and low real-time performance in the aspects of data credibility evaluation, privacy protection and security defense in the prior art are solved, and the technical effects of improving the data credibility, enhancing the privacy protection capability and improving the attack defense capability are achieved.

Methods and systems for curating data by a data manager are disclosed. Data may be curated from various data sources before being provided to downstream consumers that may rely on the trustworthiness of the curated data in order to provide desired computer-implemented services. During the data curation process, data curation resources are used to improve the trustworthiness and / or value of the collected data. However, data curation resources (e.g., data curators, computing resources) may be limited and / or insufficient to perform the data curation process as desired, which may result in unusable and / or uncurated (e.g., untrustworthy) data. Thus, the data may be screened for ambiguous values. A potential replacement value for each ambiguous value may be provided to the data source and the data source may indicate whether the potential replacement value should be used in the data pipeline as a final replacement value for the ambiguous value.

Systems and methods to enable green mining for centralized and / or decentralized financial systems are discussed. In some cases, the green mining methodologies are incorporated in distributed quantum ledger-based decentralized finance ecosystems, in decentralized financial systems and / or centralized financial systems. A proof of influence algorithm enables miners to accumulate and use reputation points to reduce computational power requirements on their systems and / or reduce energy consumptionInfluence points is an indicator of trustworthiness of the miner established based utilizing a predictive algorithm that analyzes the past mining behavior. Higher reputational scores result in lesser computationally intensive activities, which reduce energy consumption. The proof of influence algorithm rewards miners to encourage participation as validators of new blocks and / or other activities on the decentralized or centralized ledger-based systems.

Methods and systems for securing endpoint devices are disclosed. Overtime, the functionality of endpoint devices may be modified as new software is developed. To secure endpoint devices, software images of the new software may be verified prior to execution. Information usable to verify the software images may be stored in a database. A set of rules may be used to verify the trustworthiness of the software images based on the content of the database. Another set of rules may be used to verify the content of the database.

The invention provides a double-chain fusion product quality tracing method and system applied to a production line. The method comprises the following steps: firstly, collecting comprehensive data of each production node and attribute information containing a unique stage number; according to the total number of production stages, randomly selecting nodes with different numbers as initial clustering centers, and grouping all the nodes according to stage attributes by using a reverse clustering algorithm to form a node cluster; and constructing a basic traceability chain for each node cluster, and integrating data in corresponding stages to generate a distributed account book. And then screening core nodes from each basic chain to establish a cross-stage quality tracing chain, and realizing synchronous updating and inter-chain data verification of the core nodes on basic account books through an intelligent contract. And finally, a whole-process data tracing service is provided based on a quality tracing chain, and the information credibility is guaranteed by using the non-tampering characteristic of the block chain. According to the invention, product quality tracing with high reliability and high credibility can be realized.

An attestation framework to support attestation and anomaly detection in an electric grid. The attestation framework provides systems and methods that use distributed ledger technology (DLT) and implement DLT-based methods for verifying device and data trustworthiness on the electric grid. The framework attests to system changes and anomaly detection to flag specific events such as natural and cyber-induced grid events categorization, electrical faults in meters and relays and cyber events, e.g., based on statistical and baseline threshold values. The attestation framework can support the detection of system changes by itself, and in combination with an anomaly detection framework, has a lower system resource requirement and is more likely to catch system changes. An anomaly detection module can trigger attestation checks and uses the DLT for device and configuration verification purposes. The attestation framework can be deployed at substations or other environments, such as DERs or a microgrid.

The present application relates to the field of distributed computing, and discloses a data processing method, a computer device, and a storage medium, used for improving the scalability of computing resources of computing systems and reducing the block producing blockage degree of blockchains while ensuring the trustworthiness of the systems, thereby improving the block generation efficiency of the blockchains. The method is realized on the basis of a distributed computing system supporting node scaling, and the system comprises a verification node cluster, a scheduling node cluster and a computing node cluster. The system and the data processing method can improve the scalability of computing resources. Users can all use their own computers as computing nodes to provide certain computing power. A user that desires to perform computation can send a computing task to a designated scheduling node, and randomly selects a computing node on the basis of a random number seed sent by himself / herself, so that the fairness and the security of the computing task are ensured, and the identity trustworthiness of all nodes can be ensured by means of a multi-layer certificate authority mechanism.

There are provided measures for enhancement of training node selection for trustworthy federated learning. Such measures exemplarily comprise, at a first network entity coordinating artificial intelligence or machine learning contributor selection in a network, receiving, respectively from a first and a second of a plurality of second network entities managing artificial intelligence or machine learning trustworthiness in artificial intelligence or machine learning pipelines in said network, a first / second artificial intelligence or machine learning contributor selection conflict resolution request including a first / second federated learning distributed node candidate list including at least one first / second federated learning distributed node in said network, wherein each of said at least one first / second federated learning distributed node has trustworthiness capabilities satisfying first / second artificial intelligence or machine learning trustworthiness requirement criteria and is associated with a respective rank in said first / second federated learning distributed node candidate list, transmitting, respectively towards said first and said second of said plurality of second network entities, a first / second artificial intelligence or machine learning contributor selection conflict resolution response including an updated first / second federated learning distributed node candidate list removing a conflict between said first federated learning distributed node candidate list and said second federated learning distributed node candidate list.

The invention provides a credible data space construction method and system based on data sharing, and relates to the technical field of data processing.The method comprises the steps that S1, in response to a request of a user for sharing target data, credible preprocessing is conducted on the target data to obtain credible data; s2, establishing a decision-making capability model for a user to autonomously perform credible authorization on the credible data; s3, analyzing a multi-dimensional sharing risk of the trusted data; s4, planning an optimal authorization auxiliary unit sequence based on the multi-dimensional sharing risk and the decision ability model; s5, in the process that the user autonomously performs credible authorization on the credible data, sequentially executing the authorization auxiliary units in the optimal authorization auxiliary unit sequence; and S6, aggregating the credible data subjected to credible authorization to construct a credible data space. According to the method, the credibility and the security in the data sharing process are remarkably improved, and the quality of the shared data and the protection of user privacy are ensured.

Techniques for optimizing routing decisions based on security metrics within a network environment are described herein. In some cases, by using various security metrics, such as encryption indicators, attestation indicators, secureness metrics, and reliability metrics, an exemplary system can assess the security level and reliability of network paths. These metrics may provide valuable insights into the trustworthiness and integrity of participating nodes and links and enable informed decision-making regarding path selection.

The present invention discloses a blockchain-integrated financial reputation scoring system designed to assess financial credibility within decentralized ecosystems. The system generates a dynamic accountability score based on blockchain transactions, including escrow payments, invoice completions, smart contract interactions, DeFi transactions, NFT trading, and cross-chain financial activities. A risk-adaptive score weighting system dynamically adjusts the impact of financial behaviors based on transaction risk, counterparty trustworthiness, and historical financial patterns. The score is leveraged for tiered access to financial products, lending, and collateral adjustments. AI-enhanced anomaly detection prevents fraudulent score inflation, while privacy-preserving verification ensures secure reputation authentication. The system further extends into insurance underwriting, compliance verification (AML / KYC), and financial access expansion, allowing traditional institutions to assess blockchain-based creditworthiness. Quantum-resistant cryptographic techniques secure reputation data, ensuring trust and adaptability in both decentralized and traditional financial ecosystems.

The invention belongs to the technical field of block chains, and discloses a trusted query configuration method and system for block chain PB-level multi-modal data, and the method comprises the steps: obtaining multi-modal uplink data, and extracting metadata of the multi-modal data to construct an in-block index; constructing a block index table based on the block ID, logically organizing the block index table, and adaptively and dynamically adjusting the block index table; constructing an index partition table used for storing block index table identifiers and addresses; constructing a coarse-grained index model, quickly positioning a block index table in an index partition table according to query conditions, searching a reverse index in the block index table, obtaining a block ID (Identity) and a storage position, retrieving an index in a block, querying a specific data record, verifying a Hash path, and realizing credible query of data. According to the method, a decentralized self-adaptive multi-level index mechanism is adopted, decentralized query performance is optimized, complex query and traceability query operations such as connection and aggregation are supported, and effectiveness and credibility of query results are guaranteed through a credible query algorithm.

This application discloses example route selection methods, network devices, and systems. One example method includes obtaining, by a first network device, a plurality of routes arriving at a same prefixOne or more routes for guiding packet forwarding are selected by the first network device based on trustworthiness of each route of the plurality of routes, where the trustworthiness of each route identifies a trustworthiness degree of the corresponding route.

The invention belongs to the technical field of computer trusted computing, and particularly relates to a method and system for constructing a TPCM trusted root based on a multi-core BMC, and the method comprises the steps: selecting the multi-core BMC, configuring one core as a trusted core, and achieving the physical and logic isolation with other cores; tPCM related codes are integrated in the trusted core, and a TCM module is combined to provide a running environment for the TPCM; when the system is started, the TPCM performs measurement check on the BMC code and the BIOS code, and if the BMC code and the BIOS code are abnormal, a security policy is started In the system operation process, the TPCM monitors hardware, firmware and software of a calculation part in real time, and discovers abnormal behaviors to block and give an alarm; and meanwhile, the management interface is connected with a trusted management center, so that remote configuration and monitoring are realized. A multi-core BMC is used as a protection component, a server host side is used as a calculation component, and a trust chain model of a star-shaped trusted topological structure is constructed. According to the method, the TPCM trusted root is constructed by using the existing resources of the multi-core BMC, so that the hardware cost is reduced, the real-time performance of trusted measurement and the monitoring comprehensiveness are improved, and the running safety and credibility of the server are improved.

The invention relates to the technical field of communication network security, and particularly discloses a distributed communication network security verification method and system, which comprises a two-factor identity authentication module, a dynamic key arrangement and encryption module and a cross-node integrity verification module, and the dynamic key arrangement is respectively connected with the two-factor identity authentication module, the encryption module and the cross-node integrity verification module. Through combination of biological feature anchoring and secure multi-party calculation, on the premise of protecting privacy of original biological data, deep binding of biological features and public keys is realized, and biological uniqueness is given to identity authentication; and dynamic authentication interaction is fused with a timestamp, a biological characteristic entropy value and zero knowledge proof, replay attacks are resisted, 'human-equipment-identity 'consistency is accurately verified, a public key fragment is updated after authentication is passed, an identity trust chain is continuously reinforced, and it is ensured that node identities are true and credible from the source.

A computer-implemented system and method for evaluating an AI agent associated with an enterprise computing environment by aggregating a plurality of AI agents associated with the enterprise computing environment, and evaluating, with an agent evaluation unit, a selected AI agent of the plurality of AI agents using evaluation data, wherein the evaluation data includes operational behavior data and trustworthiness data. The agent evaluation unit can be configured to determine a total agent evaluation score for the selected AI agent from a plurality of category specific evaluation scores. The agent specific categories can have associated therewith a category evaluation score and the agent specific categories can include categories associated with the operational behavior and the trustworthiness of the selected AI agent. An AI-based intervention can be applied in response to the total agent evaluation score.

The present application relates to the field of big data, and relates to an active and trace back based trust management method for crowd sensing. The method comprises: acquiring task submission data of all participants, and performing standardization processing on data in each dimension; sending an unmanned aerial vehicle to an area with participant reliability uncertainty to collect data and record the data as real data; calculating the sum of difference values of data in each dimension to determine the trustworthiness of the participants; calculating the ratio of the difference value of each participant to a real value, defining a cut-off point, and determining a trust value trend of the data submitted by the participant; setting a trust value update formula; comparing traced historical data with the real data, retroactively comparing historical behaviors of the participant, and analyzing and determining the trustworthiness of the participant; calculating the amount of increase or decrease in reputation value within each timestamp; and calculating the total amount of increase or decrease in the reputation value of the participant, and determining a trust trend of the participant. The method of the present application can be used for identifying malicious participants in a system, and improving the quality of crowd sensing data.

The invention discloses a multi-tenant adaptive cooperative defense method and system in a hybrid cloud scene, and the method comprises the following steps: obtaining a remote credible proof of hardware, verifying the credibility of a tenant agent and the integrity of a code based on the remote credible proof, granting a mark, and detecting cloud information to generate a machine readable portrait containing key parameters; collecting local multi-mode log data coding embedding vectors of tenants, and after privacy processing, calculating that the abnormal confidence exceeds a threshold value by a local model to trigger current limiting or blocking; and constructing a hierarchical federated architecture containing local nodes of tenants, a regional cloud and a global control plane, encrypting aggregation parameters to generate a cross-tenant attack recognition global model and issuing the cross-tenant attack recognition global model to each tenant on the premise that log data is not out of a domain. According to the invention, integrity verification is carried out on the tenant side security agent through the trusted access mechanism, and the tenant portrait is constructed based on the trusted mark, so that the real and verifiable cooperative defense capability among a plurality of tenants is realized, and the cooperative process has dependency.

Aspects of a trustworthiness check of a video data stream are described. According to a first aspect, a unique identifier which identifies a media asset to which a portion of a video data stream to be checked on trustworthiness belongs, is included into the trustworthiness check. According to a second aspect, a certificate of a content provider for performing the trustworthiness check is retrieved from a track of editors stored at an external resource. A third aspect provides a method for identifying a portion of a video data stream to be checked on trustworthiness using a digital signature. According to a fourth aspect, a digital signature for checking a portion of a video data stream is retrieved from an external resource.

There are provided measures for trust related management of artificial intelligence or machine learning pipelines in relation to adversarial robustness. Such measures exemplarily comprise, at a first network entity managing artificial intelligence or machine learning trustworthiness in a network, transmitting a first artificial intelligence or machine learning trustworthiness related message towards a second network entity managing artificial intelligence or machine learning trustworthiness in an artificial intelligence or machine learning pipeline in said network, and receiving a second artificial intelligence or machine learning trustworthiness related message from said second network entity, wherein said first artificial intelligence or machine learning trustworthiness related message is related to artificial intelligence or machine learning model adversarial robustness as a trustworthiness sub-factor, said second artificial intelligence or machine learning trustworthiness related message is related to artificial intelligence or machine learning model adversarial robustness as said trustworthiness sub-factor, and said first artificial intelligence or machine learning trustworthiness related message comprises a first information element including at least one first artificial intelligence or machine learning model adversarial robustness related parameter.

Aspects of a trustworthiness check of a video data stream are described. According to a first aspect, a unique identifier which identifies a media asset to which a portion of a video data stream to be checked on trustworthiness belongs, is included into the trustworthiness check. According to a second aspect, a certificate of a content provider for performing the trustworthiness check is retrieved from a track of editors stored at an external resource. A third aspect provides a method for identifying a portion of a video data stream to be checked on trustworthiness using a digital signature. According to a fourth aspect, a digital signature for checking a portion of a video data stream is retrieved from an external resource.

Various systems and methods implement a decision architecture for autonomous systems. An autonomous system framework includes a safety ring configured to interface with safety features of an autonomous system; a security ring configured to provide authentication and verification services to transactions passed through the security ring; a privacy ring configured to ensure privacy of a user of the autonomous system; a trustworthiness ring configured to log and provide transparency of transactions passed through the trustworthiness ring; and a well-being ring configured to interface with the user and provide feedback and information to the user on a state of the autonomous system, wherein: each of the safety, security, privacy, trustworthiness, and well-being rings include at least one interface to at least one other of the safety, security, privacy, trustworthiness, and well-being rings.

The invention discloses a medical insurance trusted space system, which comprises a service center, a data processing center, a trusted management and control center, a technical component, a connector, an operation management layer and a supervision management layer, the service center provides a unified service entrance and business support capability for users; the data processing center is responsible for full life cycle processing and trusted computing of data; the credible management and control center guarantees credibility of participants and operations in the data space; the technical component provides bottom-layer technical tools and algorithm support, the connector realizes cross-system and cross-network secure interconnection and intercommunication, the operation management layer ensures stable operation and continuous optimization of the system, and the supervision management layer ensures compliance and risk controllability of data flow; the method has the advantages that the technology is mature and stable, the safety is high, and the whole link is controllable.

The invention discloses a power grid certificate monitoring system and method based on certificate transparency and electronic equipment, and relates to the technical field of data security, and the system comprises a CA server which is used for signing an entity of power grid equipment after receiving a request of the power grid equipment, generating a first certificate, and sending the first certificate to a server; the first certificate is sent to the power grid equipment, and a certificate chain containing the first certificate is uploaded to the CT server; the CT server is used for calculating a hash value based on certificate information of the first certificate after the certificate chain passes verification, and uploading an obtained CT log to the Ethereum server; and the Ethereum server is used for managing the CT log through the deployed intelligent contract. According to the method, the issuing and use conditions of the multi-level second certificates and the first certificate of the power grid equipment can be audited, potential security threats are detected in real time, and the security and trustworthiness of the CT server can be effectively monitored by storing the certificate transparent log into the third-party security data storage-smart contract.

The invention discloses a smart city cloud platform data authorization sharing method and system based on a block chain, and relates to the field of data sharing, and the method comprises the steps: responding to a received query instruction of an access user, and determining the historical query information of the access user through a smart city cloud platform; performing identity verification on the access user based on a preset identity registration chain, and if the access user passes the identity verification, evaluating a trust value of the access user according to the historical query information; performing trust degree verification on the trust value; if the access user passes the trust degree verification, constructing a puncturable key structure in combination with the trust value of the access user, a preset ABAC model and a preset smart city alliance chain; and performing dynamic authority management on the access user by using the puncturable key structure, performing identity authorization on the access user based on the puncturable key structure, and sharing data queried by the access user. The management efficiency of the smart city can be effectively improved.

Described herein are systems, methods and instrumentalities associated with a trustworthiness evaluation framework for determining the trustworthiness of a wireless transmit / receive unit (WTRU) to participate in a network operation such as an artificial intelligence machine learning (AIML) operation. The framework may provide capabilities for monitoring, evaluating, and / or selecting the WTRU to participate in the network operation. The trustworthiness of the WTRU may be evaluated based on data and / or analytics such as the privileges and security state of the WTRU, security policy rules, the behavior history of the WTRU, the attributes and / or reputations of the WTRU, referrals for the WTRU from other entities, etc. A trustworthiness level or score may be determined to indicate the trustworthiness of the WTRU. An access policy may be dynamically formed and / or enforced to reflect the trustworthiness of THE WTRU.

A method for checking a video data stream having a video encoded thereinto on trustworthiness comprises: subjecting a predetermined portion of the video data stream, or data derived therefrom, to a hash function to obtain a hash value; deriving a digital signature from the video data stream; and checking whether the hash value fits to the digital signature to determine whether the video data stream is trustworthy.

The invention discloses an intranet security block chain auditing method based on secure multiple parties, and the method comprises the following specific steps: 1, generating a secret key: enabling a participant to initialize and generate secret mark information, and generating a personal private key, a personal public key, a group public key and a group private key; 2, establishing a credible mechanism, and evaluating the mechanism through dynamic credibility; step 3, signature generation: the participant generates a signature of the message by using the personal private key and public key and the group public and private key; 4, signature verification: verifying the validity of the signature by using the group public key; 5, dynamically updating and regularly updating secret mark information and a private key of a participant to improve system security, and 6, block chain auditing: encrypting a trust evaluation matrix and storing the trust evaluation matrix in a block chain by an agent to facilitate subsequent auditing and verification, and performing encryption storage on the trust matrix by selecting a semi-trusted agent and performing decryption verification when needed, thereby improving system security. And the credibility of participants is ensured.