290 results about "Trust level" patented technology

The invention discloses an agricultural data intelligent contract cross-domain sharing method based on a master-slave chain, and particularly relates to the technical field of agricultural data sharing. Edge computing nodes are deployed through a slave chain, multi-source heterogeneous agricultural data are collected, a dynamic trust level model is constructed, credibility evaluation and screening are performed on the data, and highly-credible data are synchronized to a main chain for sharing; the low-credibility data is reserved in slave chain verification; the main chain realizes transparency of a data sharing rule based on a smart contract, constructs a dynamic risk prediction model in combination with a space-time convolutional network, performs probability distribution prediction on a crop abnormal coefficient, optimizes a resource allocation scheme, and triggers hierarchical early warning by using the smart contract to realize efficient allocation and dynamic optimization of cross-regional resources; the problems of sharing obstacles, insufficient data credibility and inaccurate resource allocation caused by agricultural data isomerism in the prior art are effectively solved.

The invention discloses a zero-trust data access control method and system and a storage medium, and the method comprises the steps: carrying out the identity authentication of a user logging in a client, and obtaining the current terminal equipment information of the client, the current network information and the historical access information of the user after the authentication succeeds, the trust level of the authorization request and the current access permission matched with the trust level are obtained; acquiring a real-time access action of a user and real-time terminal equipment information and real-time network information of a client to perform threat detection on the authorization request, and adjusting the current access permission so as to generate a real-time access strategy corresponding to the client according to the adjusted real-time access permission; and acquiring a data access request uploaded by the client according to the real-time access strategy, acquiring access data required by the client according to the access request, and sending the encrypted access data to the client, thereby improving the security of data access.

The invention relates to the technical field of big data analysis, in particular to an operation management system and method based on financial marketing big data, and the system comprises a data standardization module, a customer portrait disambiguation module, a strategy matching module, a real-time transmission module and an operation strategy generation module. According to the method, a data table with a unified structure is constructed through combined judgment of field semantics and numerical rules, the data consistency is improved, customer information integration is executed based on field conflict time, credibility level and logic verification, the recognition accuracy is enhanced, and the matching relation is judged by combining the transaction amount, the product association degree and the interaction frequency with strategy attributes; according to the method, strategy dynamic screening is achieved, pushing content is screened according to the strategy emergency degree and the channel state, the transmission efficiency is improved, customer clicking, conversion and feedback participate in behavior trend judgment, strategy updating linkage is supported, an overall processing chain is of a closed-loop structure, and the fusion accuracy and the strategy response timeliness are improved under the conditions of data fragmentation and multi-source heterogeneous.

The invention provides a credible industrial agent task distribution method and system, and relates to the technical field of data processing, and the method comprises the steps: receiving a registration request sent by an industrial agent developer, and storing the metadata information of an industrial agent into a distributed account book based on the registration request; and based on the metadata information, receiving a task distribution request sent by a task requester, and matching candidate industrial agents and unique identifiers meeting function requirements in a distributed account book. Credible agents are screened through distributed account book evidence storage core information and dynamic trust evaluation, the credibility level is iteratively updated after execution, and credibility traceability of the whole task distribution process and dynamic optimization of the credibility of the agents are achieved.

A system and method for privacy-preserving communication validation and multi-attribute trust scoring is disclosed. The system analyzes communication metadata to determine pattern legitimacy by comparing current communication patterns against relationship fingerprints without accessing communication content. The system validates relationship context between communicating parties using interaction graph analysis and historical communication data. Cross-network intelligence correlation compares current patterns against aggregated patterns across voice, email, and messaging services, creating a self-strengthening security framework that recognizes emerging threat patterns while validating legitimate communication behaviors. The system generates comprehensive multi-attribute trust assessments comprising individual trust attribute scores including engagement rate, reliability index, channel preference, temporal pattern, and behavioral pattern, combined into overall trust levels. Trust context is displayed through a user interface presenting simplified, intuitive, and actionable information with progressive disclosure capabilities, enabling informed user decisions while preserving privacy. Communication processing actions provide users with appropriate engagement options tailored to specific trust assessment results.

The invention discloses a CRITIC-based man-machine cooperation system trust degree evaluation method, and belongs to the technical field of man-machine interaction and human factor engineering, and the method comprises the steps: S1, obtaining the physiological data and flight data of a pilot when the pilot executes a manned and unmanned system task; s2, preprocessing and standardizing the physiological data and the flight data respectively; s3, weight calculation is carried out based on a CRITIC method, and standardized multi-dimensional feature data is used as input of a CRITIC model and is used for calculating objective weights of all indexes; and S4, calculating a credibility value by using the generated weight matrix. By adopting the CRITIC-based man-machine cooperation system trust degree evaluation method, objective real-time quantitative evaluation is realized; the weight is adaptively determined according to the data features, the method is more scientific than artificial experience, physiological and behavior data are fused to capture psychological changes, the trust level can be monitored, the cooperation strategy is adjusted accordingly, and the task safety and efficiency are improved.

The invention belongs to the technical field of Internet of Things security, and particularly relates to a multi-level Internet of Things equipment security management and access control method, which comprises the following steps of: performing bidirectional verification on a digital certificate and a hardware fingerprint through an edge node when equipment is accessed; calculating credibility in real time and dynamically dividing security levels by using a hybrid evaluation algorithm based on equipment operation context data; a fine-grained access strategy is generated in combination with equipment attributes and environmental risks, and cross-level collaboration is realized through a lightweight protocol; abnormal behaviors are detected in real time in the access process, and high-risk operation is blocked within milliseconds; and strategy conflict resolution and adaptive optimization are realized through formalized verification and deep reinforcement learning. According to the technical scheme, the identity authentication reliability, the authority dynamic adaptability, the strategy consistency and the threat response speed of the Internet of Things equipment are remarkably improved, and a systematic security guarantee is provided for large-scale Internet of Things applications with high security requirements.

The invention relates to the technical field of network security monitoring, in particular to a multipath network communication security guarantee method based on an adaptive encryption algorithm, comprising: acquiring a network undirected graph corresponding to a target network, the network undirected graph comprising a first node set, a second node set and an undirected edge set, the first node is used for collecting and managing data, the second node is used for monitoring the safety state of the first node, and the undirected edge is used for connecting the first node and the second node. According to the method, the behavior of the second node in the network is subjected to feature extraction, the trust level of each node can be dynamically evaluated and adjusted in combination with the pre-trained trust classification model, and the self-adaptive feature can effectively adjust the communication security level according to the actual situation, so that the security of the network is improved, and the user experience is improved. And potential security threats or malicious nodes can be identified by monitoring and analyzing the behavior of the second node.

The invention relates to the technical field of ship navigation and data safety, solves the technical problem that an existing ship data safety guarantee system has defects in the aspects of data trust evaluation and data correction, and particularly relates to a safety guarantee method for credible interaction of inland ship shore-based driving control data under a zero-trust architecture. Comprising the following steps: standardizing operation data to obtain ship sensing data and shore-based data with the same dimension; based on an evidence theory, taking the ship sensing data and the shore-based data as independent evidence sources to perform fusion processing so as to obtain a trust evaluation result for quantitatively representing data credibility; and performing consistency correction on the ship sensing data and the shore-based data based on a least square method. According to the method, scientific and rigorous trust evaluation is realized, mathematical optimality of data fusion is guaranteed, and long-term reliability is ensured. Meanwhile, the credibility and the weight are directly associated with the equipment precision and historical data, so that an operator can flexibly adjust the system to adapt to different equipment.

The invention discloses a distributed computing task scheduling security guarantee method and system based on dynamic trust evaluation, and the method comprises the steps: collecting and preprocessing the operation state data of each computing node in real time, and dynamically calculating and updating the trust degree of each node according to the operation state data; according to the credibility and in combination with node resource loads, the tasks are only allocated to nodes with the credibility not lower than a preset threshold value and sufficient resources to be executed; the node state is continuously monitored in the task execution process, when a node fault is detected or the node trust degree is lower than the threshold value, task rescheduling is triggered, and the affected task is migrated to the remaining nodes with high trust degree and sufficient resources to continue to be executed; the key data of task allocation, node selection and task completion state are written into the block chain by using the characteristics of decentralization, non-tampering and encryption protection of the block chain so as to ensure the transparency and data security of the task execution process.

The invention relates to the technical field of data center resource scheduling, and discloses an intelligent data center optimization method based on distributed GPU computing power scheduling. According to the method, historical scheduling records are quantitatively evaluated, historical strategies are distributed to experience groups of different levels according to scheduling effect indexes and strategy trust levels, and a structured strategy library is formed. And for a target performance level defined in the dynamic behavior model of the data center, calculating a serialized scheduling scheme for achieving a target, and selecting candidate strategies from the structured strategy library. And carrying out adaptive correction on the serialized scheduling scheme and the candidate strategy by adopting a fusion decision-making method to generate a final scheduling strategy. And executing the final scheduling strategy, generating a control command in combination with the real-time resource data to implement resource adjustment, and recording an actual performance result. By comparing the deviation between the actual performance result and the target performance level, the deviation source is diagnosed, the experience grouping content is revised, and the structured strategy library is optimized.

The invention belongs to the technical field of data security, and particularly relates to a trust-based Internet of Things data security system, which comprises a hierarchical trust evaluation module used for converting equipment identity legality, data integrity and behavior compliance into quantifiable trust values through an identity-data-behavior three-dimensional model; and the dynamic trust updating module is used for realizing periodic updating of trust values, linkage authority control of trust levels, and abnormity repair and access blocking of low-trusted equipment according to trust data acquired in real time, and ensuring synchronization of a trust state and an actual safety condition of the equipment. According to the invention, a multi-factor identity authentication mechanism of equipment hardware fingerprint + dynamic token + cloud identity verification is constructed through the hierarchical trust evaluation module, so that equipment identity credible verification is realized, and the risks of identity counterfeiting and certificate leakage are resisted.

The present invention relates to a method for evaluating the driver trust level of an L3-level autonomous vehicle, which includes the following steps: Step 1, by introducing a subjective trust scale, obtain the driver trust level of the autonomous driving takeover experiment and conduct a quantitative analysis on the subjective trust level; Step 2, use the K-means clustering method to classify the subjective trust level; Step 3, extract the key frames of the driving takeover; Step 4, encode the extracted driver states; Step 5, establish a driver trust level evaluation method based on the Kalman filter algorithm. The present invention can provide a reference for the objective and real-time evaluation of the driver trust level in emergency takeover scenarios, which is beneficial to improving the safety and reliability of autonomous vehicles.

The invention discloses a total-factor integrated large Token data management system, and the system comprises an identity credential collection unit which is used for obtaining an identity label and associated business data from a plurality of social subjects; the identifier abstraction unit is used for mapping the identity identifier into a standardized Token primary key according to a main body type and structuring the associated business data into a corresponding digital asset package; the total element aggregation unit is used for aggregating and packaging the digital asset package into a single verifiable large Token data structure, and the large Token comprises a Token primary key and a dynamic trust level; the dynamic trust engine is used for calculating and updating the trust level of each main body in real time and binding the trust level to the corresponding large Token; and the intelligent service execution unit is used for responding to an external business instruction and calling the large Token to realize intelligent service.

An electronic device and a method of operating an electronic device comprising processor circuitry is disclosed, the method comprising receiving media data associated with a media stream, the media data comprising one or both of audio data representative of audio and video data representative of video; determining a trust level associated with the media stream based on the media data; and providing an output indicative of the trust level.

A device includes a plurality of chiplets. At least one pair of chiplets of the plurality of chiplets is coupled to one another. Each chiplet of the plurality of chiplets includes a Root-of-Trust (RoT) circuit and a trust level mapping circuit. For each chiplet of the plurality of chiplets, the trust level mapping circuit of the chiplet is configured to modify trust levels of transactions received from a different chiplet of the plurality of chiplets.

The invention relates to the technical field of maritime monitoring electronic fences, in particular to a maritime electronic fence internet monitoring method and system, and the method comprises the steps: receiving a structured operation intention statement; obtaining associated historical behavior records; according to the historical behavior record, evaluating the trust level of the ship management party; inquiring whether an effective structured operation intention statement related to the current ship in time and space exists or not; if yes, according to the trust level of the current ship, judging that the judgment result of the deviation behavior belongs to an in-plan deviation or illegal behavior; if not, the property of the deviation behavior is judged according to the electronic fence basic rule set. The method has the advantages of obviously reducing the workload of manual verification and improving the monitoring accuracy and efficiency by intelligently distinguishing in-plan deviation and real violation.

A distributed resource automatic matching method based on credibility grading comprises the steps that multi-dimensional operation performance indexes of edge nodes of a distributed power grid are collected, a node initial credibility evaluation value is generated through quantitative calculation, and a node credibility initial model is constructed; capturing a node operation behavior change trend based on a sliding time window, adjusting each performance index evaluation weight according to a node data fluctuation amplitude, calculating a dynamic trust degree evaluation value by combining a dynamic weight mechanism, dividing the nodes into at least two trust levels according to a preset threshold value, and mapping the nodes of different levels to corresponding physical regions; when a regulation and control task is responded, candidate resources are preferentially matched from high-trust-level nodes, and resource scheduling deployment is completed in combination with task urgency and node electrical characteristic related factors; after the task is completed, the dynamic credibility evaluation value of the node is corrected based on the actual execution effect evaluation result of the node, the corrected evaluation value is used for updating the node credibility model and subsequent resource matching, and a closed-loop feedback mechanism is formed.

The invention discloses a zero-trust-based WAPI electric power communication security access method and system and a storage medium, and the method comprises the steps: carrying out the identity authentication of a terminal device, the identity authentication comprising certificate authentication and biological feature authentication, and the biological feature authentication comprising fingerprint authentication; if the identity authentication is passed, starting a dynamic access strategy for the network based on the trust level; monitoring an identity authentication process and a dynamic access process in real time, and continuously performing risk assessment to obtain a risk assessment result; and granting dynamic access authority or directly terminating access based on an evaluation result. According to the invention, through dynamic fingerprint authentication and dynamic granting of the access authority, fine-grained access control is carried out on resources while the security is ensured, the reliability and service continuity of the system can be improved, and unauthorized access and potential network attacks can be effectively prevented.

The invention discloses a rehabilitation nursing robot interaction regulation and control method based on a man-machine trust feedback mechanism. The method comprises the steps that expression, voice, physiology and behavior data of a user are collected through a multi-mode sensor; constructing a trust evaluation model, and predicting a user trust value in real time; according to trust level matching interaction strategy parameters, dynamically adjusting information transparency, control right distribution and interaction frequency; a rehabilitation task is executed, feedback signals are collected, the model is optimized, and self-adaptive learning is achieved. The system forms a closed loop structure of perception-evaluation-regulation-execution-feedback-optimization, and has humanization, individuation and dynamic adaptive capacity. According to the method, the trust degree and participation sense of the user on the rehabilitation nursing robot are improved, the rehabilitation compliance is improved, and the method has good clinical application prospects and popularization value.

A computer-implemented method performs dynamic filtering within a service mesh. While transferring data from one microservice to another microservice, each microservice evaluates a level of trust with each upstream and downstream microservice based on the level of trust score. Each microservice evaluates which data should be filtered while transferring data to downstream microservice and which data should be filtered while receiving data from upstream microservice.

A method for processing schedule information and a first electronic device for implementing the method are disclosed, relating to the field of communication technology. The method includes: the first electronic device receiving a first message sent by a second electronic device, the first message carrying the trust level of the second electronic device; determining whether the trust level of the second electronic device meets the preset conditions; and when the trust level of the second electronic device meets the preset conditions, the first electronic device sending a first schedule to the second electronic device. By adopting this technical solution, selective schedule synchronization can be achieved.

The invention discloses a PCIe network-based hardware communication method supporting path encryption and device authentication, a switching device and a switching system. The hardware communication method comprises the following steps: setting a device authentication module, a path control module and a path execution module in the switching device of the PCIe network; the equipment authentication module is used for acquiring hardware information of all source equipment and target equipment and establishing a trust level table; the path control module is used for traversing all source equipment and target equipment according to the trust level table, and constructing a path strategy table by using a preset path rule; and the path execution module is used for judging each path between the source equipment and the target equipment according to the path strategy table and executing data processing. Dynamic path control based on the device identity and the trust level is achieved, a fine path strategy can be generated according to the trust state of the source device and the target device, and path control over the level by the device is achieved.

The invention provides an access control method and an access control system based on satellite internet application, which are used for improving the reliability and the security of satellite internet application center platform resource security protection. The access control method based on the satellite internet application comprises the following steps: after an access request is received, performing identity authentication on a satellite terminal and a user according to information carried by the access request; if the authentication is not passed, refusing the access request; if the authentication is passed, collecting related state data about satellite terminal attributes, user attributes and application access resource attributes through a situation awareness technology according to information carried by the access request, and performing comprehensive trust evaluation on the satellite terminal according to the collected related state data; and matching the comprehensive trust evaluation result to a corresponding trust level, and comparing the matched trust level with a preset access request trust level to realize access control. According to the invention, the reliability and security of satellite internet application center platform resource security protection are improved.

A method includes: receiving an integrated circuit design; classifying, by the processing device, a signal path of a sub-circuit of the integrated circuit design based on a connection between an input port of the signal path and a component of the sub-circuit to generate a classification of the signal path; computing, by the processing device, a security vulnerability result of the sub-circuit of the integrated circuit design based on the classification of the signal path and based on a trust level of a zone in a fan-in cone to an input port of the signal path; and generating a security vulnerability report based on the security vulnerability result of the sub-circuit of the integrated circuit design.

According to the PLC trust level division method oriented to the control process and the data, the problem of credibility evaluation of internal process operation logic and associated data thereof in the PLC operation process is solved, and comprehensive division of PLC trust levels is achieved. Firstly, a fuzzy neural network is used as a carrier of a data driving model, a PLC trust level prediction model is constructed, model parameters are adjusted on line according to variable data such as PLC internal process operation behaviors, network flow and data integrity, and accurate prediction of the trust level in the PLC operation process is achieved; secondly, a lightweight neural network mechanism and a self-adaptive neural network structure are provided, the calculation complexity of a PLC trust level prediction model is effectively reduced, and the speed of PLC trust level prediction is increased; finally, the trust score of the PLC in the operation process is predicted in combination with the model, and rapid and accurate prediction of the trust level of the PLC in the operation process in the industrial production process is achieved.

The invention discloses a yellow storm terrorism content identification and filtering method and system, and relates to the technical field of digital content auditing, and the method comprises the steps: carrying out the modal decomposition and preprocessing of a to-be-detected content, including the calculation of a single-modal sensitive probability and confidence, and recording the coordinates and confidence of a local image region; calculating a dynamic weight and performing normalization processing based on the confidence and the prior credibility of each mode; calculating a final fusion score by combining the sensitive probability and the weight of each mode, and performing content auditing decision according to a preset threshold value; and the modal priori credibility is updated through manual feedback data. According to the method, the detection rate of cross-modal violation contents is remarkably improved through a multi-modal collaborative analysis and confidence-driven dynamic fusion technology; and the system adopts a three-level decision-making mechanism to automatically allocate auditing resources, so that the manual rechecking cost is greatly reduced, meanwhile, an online learning function is introduced to continuously optimize the model, the sensitivity to novel violation contents is kept, and the processing efficiency and detail identification are both considered.

The present technology provides for receiving communications at an authentication service, and the communication is indicative of a change in a security posture of an authenticated session between a user device and a secure service. The authentication service can then determine that the change in the security posture of the authenticated session impacts the trust level associated with the user device and causes the trust level to fall below the threshold. The authentication service can then send an enforcement signal to a security agent on a network device that provides remedial actions that a user can undertake to improve the security posture of the authenticated session.