222 results about "Trust relationship" patented technology

The invention relates to the technical field of network security, in particular to a network intrusion detection method and system based on behavior analysis, and the method comprises the steps: collecting real-time data of a target network, the real-time data comprising network flow data, user access logs, equipment state parameters, inter-user interaction logs and trust relationship data; performing space-time correlation analysis on the real-time data to generate a dynamic behavior graph; performing anomaly detection on the dynamic behavior map to generate an abnormal node list; and executing attack blocking based on the abnormal node list. According to the invention, the recognition and defense capabilities of abnormal behaviors are effectively improved.

A method of authorizing a computer mouse to perform a particular action may include receiving, by a network device, a request associated with a particular action to be performed by a computer mouse. The request may be digitally signed using a private device key of the computer mouse. The method may include validating, by the network device, the digitally signed request using a public device key previously provided by the computer mouse. The method may include generating a response to the request. The response may indicate whether the computer mouse is authorized to perform the particular action associated with the trusted request. The method may include sending the response to a client device associated with the computer mouse.

The invention discloses a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform, which relates to the technical field of logistics transportation, and comprises the following steps: establishing a trust mechanism with a user accessing the cloud computing platform, establishing a long-term trust relationship under the trust mechanism, and performing credit scoring through a preset algorithm model; the logistics resource sharing database is used for dispersedly storing logistics resource data on a plurality of physical or virtual nodes by adopting a distributed storage technology, collecting user information related to node information before the information in any node is called, and verifying the authenticity of the user information; the method is used for cooperatively scheduling related data passing verification in the logistics resource database. According to the method, long-term cooperation and resource sharing among users are promoted by constructing a trust mechanism and a credit scoring system, and efficient integration and rapid access of resources are realized by combining a logistics resource sharing database constructed by a distributed storage technology.

The invention discloses an intelligent decision-making method and system based on deep learning, and relates to the field of data processing. The method comprises the steps of obtaining place data and corresponding attribute data of a to-be-decided project; establishing a fuzzy relation matrix between the places and the attributes; generating a network model reflecting trust relationship strength among users through trust propagation operation of the graph neural network; identifying a community structure containing a community overlapping degree through a community discovery algorithm; and according to the trust relationship strength between the users and the community overlapping degree, calculating an influence weight of a decision maker, forming a group consensus through a robust optimization method, and generating a decision result of the project to be decided. Aiming at low network relation modeling precision caused by multi-source heterogeneous data in bus station layout decision making in the prior art, the method and the device have the advantages that the network relation modeling precision is low through accurate modeling of an information propagation path in a complex trusted network, effective dimension reduction representation of a high-dimensional feature space and robust optimization solution in an uncertain environment; therefore, the calculation precision and robustness of the bus station layout intelligent decision-making system are improved.

A serving network establishes a connection with a UE via an N3AN using a trusted registration procedure to establish a secure access link between the UE and the serving network via the N3AN. The serving network sends a trust indication message via the N3AN to the UE using the secure access link to identify the N3AN as trusted or untrusted. When the received trust indication message indicates the N3AN is untrusted, the serving network executes an untrusted registration procedure with the UE using the secure access link to establish the connection between the UE and the serving network. When the received trust indication message indicates the N3AN is trusted, the serving network continues execution of the initial registration with the UE using the trusted registration procedure to establish the connection between the UE and the serving network. The UE and serving network exchange messages via the established connection.

Determining when and / or how to execute a program or script published to a blockchain network may rely on data that is external to the blockchain (i.e., external data) such as data about the real-world state and events. A prover (e.g., a node of the blockchain network) may perform one or more computations on behalf of a client, such as the execution of the program. To execute the program properly, the prover may rely on external data, which the prover may obtain from a data provider that has a trust relationship with the client (e.g., the client accepts as valid data provided by a trusted data provider). Systems and methods described herein may be utilized by a prover to provide cryptographically verifiable assurances of the authenticity of input data purportedly obtained from a data provider, the input data utilized in the execution of a program or script published to a blockchain network. An example of a blockchain network is a Bitcoin-based network.

The invention discloses a decentralized trust relationship collaborative prediction method and a related device, and the method comprises the steps: starting a block chain system, publishing a public safety parameter and an initialization model on a block chain, and loading a consensus algorithm at a consensus node; constructing a local complete graph by using local data, pre-training the local graph to obtain a user feature extraction and relationship prediction model, and obtaining features of user nodes; establishing a public graph based on the public knowledge, sending the public graph to a block chain consensus node, and performing consensus confirmation on the public graph; and outputting a final trust relationship prediction model. The invention discloses a decentralized trust relationship collaborative prediction method based on federated learning and a graph neural network, and aims to solve the limitation of a traditional trust evaluation method in a multi-source distributed scene and improve the accuracy of trust relationship prediction.

A method, performed by at least one processor of a trust broker, for establishing trust of vendor-supplied Open Radio Access Network (O-RAN) software, includes: receiving a plurality of O-RAN software from a plurality of O-RAN software vendors, the plurality of O-RAN software respectively signed by the plurality of O-RAN software vendors; for a software, among the plurality of O-RAN software, verifying a signature included with the software using a vendor certificate issued by a certificate authority (CA) of the corresponding vendor; based on successful verification of the signature, performing a software attestation with respect to the software using a digital certificate issued by a CA of the trust broker; and providing the attested software to an operator corresponding to the O-RAN system and with which the trust broker has a trust relationship.

The invention discloses a data encryption method applicable to open source gap terminal equipment, which comprises the following steps of: firstly, establishing communication connection based on a gap distributed soft bus technology, and generating a trust relationship through identity identification authentication; during data transmission, a national cryptographic algorithm, a symmetric or asymmetric encryption algorithm, a hybrid encryption algorithm and the like are dynamically selected according to data types, importance, transmission scenes and equipment performance. After being encrypted, the data are transmitted to the target device through the soft bus, and the target device decrypts and verifies the data. And the terminal equipment is integrated with the hardware security module to realize hardware encryption and key storage. Security module adaptation development is carried out based on an HDF library, and one-time development and multi-terminal operation are achieved. In the encryption process, a fragmentation encryption strategy can be adopted, multiple devices can perform collaborative encryption and decryption, and the encryption efficiency is improved by defining the task priority and sequence and utilizing a distributed task scheduling mechanism and reasonably allocating resources.

Information security systems and methods are presented including synchronized state machines operating with private data and tamper-evident identifiers that expand the problem space of attacks by unauthorized consumers of data in flight or rest to near infinity. A quantum cryptography-resistant distribution network for identity, trust relationship, encryption, and transcoding of valuable information is described where a priori knowledge of the hardware or software is irrelevant to the safe time for the data protected and modified as needed within a multikey encryption and data control and availability assurance domains. Due to its low compute design, the methods described within are well suited for a variety of tasks including real-time data streams such as video and audio distribution.

The invention discloses a transnational trust modeling method fusing quantum state mapping and language phase difference, comprising the following steps: 1) estimating the site of each country based on the voting data of the united countries, and calculating the trust weight between countries through a weighting function in combination with the political ideal point distance and voting consistency of each country to obtain the initial quantized value of transnational trust; 2) mapping the initial trust value to a quantum state on a Bloch ball, applying phase perturbation according to semantic difference reported by a core country media, and simulating trust interaction between countries under discourse difference in combination with a quantum game mechanism so as to obtain a trust value mapped back to a classical space; and 3) carrying out iterative updating on the trust value by adopting a social influence model, dynamically describing an evolution process of the trust relationship between the countries, and outputting a time sequence change result of the trust network between the countries. According to the method, by fusing the international voting behavior and the transnational utterance difference, dynamic and quantifiable modeling of the inter-country trust relationship is realized, and an innovative methodological support is provided for international relationship research, transnational strategic game analysis and global risk early warning.

The application discloses a computing power scheduling system and method of a computing power network, relates to the technical field of computing power distribution and scheduling, and comprises the following steps: acquiring all computing power nodes in the computing power network and constructing a computing power node interaction network model; acquiring a computing power task initiating node and computing power task attributes; determining a target attribute group cluster of the computing power task based on the computing power task attributes, and recording all computing power nodes in the target attribute group cluster as demand target nodes of the computing power task; determining an execution trust target node of the computing power task based on the computing power task initiating node; finding an intersection of the demand target nodes of the computing power task and the execution trust target node of the computing power task, and recording the intersection as a comprehensive target node; and determining an execution computing power node of the computing power task from the comprehensive target node in combination with balanced load. The application has the advantages that the interaction network model of the cooperative trust relationship and the attribute group cluster is constructed, multi-dimensional node dynamic screening and optimized matching are realized, and the efficiency and reliability of the computing power scheduling are significantly improved.

To provide a business support system that builds a relationship of mutual trust between the facility hosting the event and the exhibitors, centralizes information about the group to which the facility belongs, and improves convenience for both parties in a series of procedures for hosting an event and opening a tenant store. [Solution] A business support system accessible to users including facility personnel, shop owners who can set up shop in spaces within the facility, and managers, the business support system having a server including a control unit and a storage unit, The memory unit includes information on users, facilities, and exhibitors. The control unit includes an extraction unit that extracts information from the storage unit in response to a user request; a display data generating means for generating display data for displaying the information extracted by the extracting means in a form that satisfies a user's request; A display data output means for outputting the display data to a terminal; A business support system with the above features.

The invention provides a cooperative crowd sensing team recruitment method and system based on multi-view trust, and belongs to the technical field of crowd sensing. According to the method, a multi-view trusted network is constructed based on an interaction relationship and attribute data of node users; constructing an extensible trust evaluation model based on the graph attention network, and mining a multi-view trust relationship between node users in the multi-view trust network; obtaining a multi-view trust expectation of a specific task, and integrating a multi-view trust relationship between node users into global trust of the specific task; the method comprises the following steps: constructing a team allocation target function by taking a high global trust value in a specific task as a target, solving the target function by using an alternate iteration solving method to obtain an optimal solution, and obtaining an allocation result of a cooperative crowd sensing team through the optimal solution. According to the method, the optimal team can be recruited for the specific task by integrating a plurality of trust relationships on the basis of remarkably reducing the calculation amount, and each user is ensured to be matched with the optimal collaborator.

The invention provides a hybrid encryption method and device and a storage medium, and the method comprises the steps: a client generates a short-term SM2 key pair and exchanges with a server after obtaining a long-term SM2 key pair and a server public key, dynamically generates a session SM4 symmetric key through an SM2 key exchange protocol, and finally achieves the data transmission and response processing through the session SM4 symmetric key. Through the implementation of the scheme of the invention, the client not only establishes the basic trust relationship based on the long-term SM2 key pair, but also generates the short-term SM2 key pair during each service request, and dynamically derives a unique session SM4 symmetric key and an initial vector by cooperatively executing the SM2 key exchange protocol with the short-term key of the server. And each request has an independent security context, so that the decryption risk after the session key is reused or stolen is fundamentally prevented, and the end-to-end dynamic security communication under the national secret system is really realized.

The invention provides a trust information missing trust feature complementation and trust relationship prediction method and system, and the method comprises the steps: constructing a social relation graph and a trust relation graph, and obtaining social attribute features and trust attribute features respectively; compressing the social attribute features and the trust attribute features, and constructing a feature converter to convert the compressed social attribute features; constructing a user trust relationship prediction model, and outputting a prediction label by taking the compression characteristics of the user as input; taking the converted and compressed social attribute features as input, and outputting a prediction tag; and taking a real label as supervision information, combining reconstruction loss and information bottleneck loss, training the model, and outputting a trust relationship. According to the method, the social behavior graph and the trust relation graph are constructed, and the social attribute characteristics and the trust attribute characteristics of the user are learned respectively. According to the multi-view learning mode, the feature information of the user can be more comprehensively captured, and the accuracy of trust relationship prediction is improved.

The invention relates to an exoskeleton safety redundancy strategy and switching method based on anomaly detection, and the method comprises the steps: collecting a tension state between the active control intention of a user and the response execution of an exoskeleton system, defining as a potential anomaly when continuous asynchronous tension exists between the expected control direction of the user and the inertial behavior of the system; a redundancy strategy triggering precondition is adopted; after abnormal triggering, the system outputs a control suggestion, and whether the control right should be taken over by a redundancy strategy or not is judged by combining user reverse force application and posture deviation trend behavior performance, and master control continues to be maintained or a forced freezing state is entered; the intervention level of a redundancy control strategy is dynamically adjusted, and continuous control evolution from low intrusion to high takeover is achieved; if it is detected that an irreconcilable confrontation trend exists between continuous reverse intention input of the user and control output of the system in the control evolution process, and intervention ratio unbalance of the system is continuously expanded, the system enters a soft freezing or conservative attitude mode; and in the freezing state, judging whether the man-machine trust relationship is reconstructed or not.

The invention relates to a three-camera linkage and intelligent evaluation eight-brocade intelligent scoring system based on machine learning and a sum-product method. In an eight-section brocade scoring scene, a traditional subjective scoring mode has many defects. In order to solve the problems, an intelligent scoring system is constructed. The system comprises a video data acquisition module, a posture recognition module, an intelligent scoring module, a score integration module and the like. The video data acquisition module acquires multi-angle videos through three high-definition cameras; the posture recognition module accurately recognizes actions by using an advanced algorithm and a deep neural network technology; the intelligent scoring module designs a multi-dimensional index, and scores based on a sum-product algorithm; and the score integration module gathers scores from different perspectives to obtain a comprehensive score. According to the method, various measures are adopted to overcome the limitation of the existing AI technology in sports detection, including environment optimization and action detail identification, construction of a diversity and balance data set, research of cross-group adaptability, establishment of a man-machine cooperation trust relationship and the like. The system improves objectivity, accuracy and fairness of eight-segment brocade scoring, and is of great significance to eight-segment brocade teaching and competition. Meanwhile, a new technical means is provided for the fields of physical education and detection, the application range of the artificial intelligence technology in the field of physical education is expanded, and fusion innovation of the AI technology and the traditional field is promoted.

The invention discloses a safety communication device based on artificial intelligence, which comprises a processor, and the processor is connected with an encryption module, an identity verification module, an intrusion detection module, a machine learning module, a safety protocol module and a user interface module. The invention belongs to the technical field of intelligent communication, through the combination of the encryption module and the identity verification module, a trust relationship and a data encryption transmission channel can be established between two communication parties, the data security and integrity can be improved, potential malicious activities are monitored and identified in real time through the intrusion detection module, and the security of the communication parties is improved. Hacker attack and data leakage can be effectively prevented, meanwhile, through continuous learning and optimization of the machine learning module, the system can adapt to a new threat mode, flexible security configuration and management are provided, the overall security performance is improved, and the market prospect is wide.

In at least one example, a method includes establishing, by a sniffer provisioning server (SPS) of a first wireless device, a trusted relationship between the first wireless device and a sniffer tool using a public key of the sniffer tool. An out-of-band (OOB) key exchange provisions the public key of the sniffer tool to the wireless device. The method further includes obtaining, by the SPS, key material uniquely related to a communication session established between the first wireless device and a second wireless device using a shared password. The key material excludes the shared password and a session key uniquely related to the communication session. The method further includes publishing, by the SPS, the key material over a channel to the sniffer tool based on the trusted relationship. The channel is secured using the public key of the sniffer tool.

The invention discloses a social network trust evaluation method and system based on a multi-view graph neural network, and the method comprises the steps: obtaining social network behavior information, constructing social behavior network graphs of different views, and constructing a user trust relationship network graph according to the trust relationship between users; based on social behavior network diagrams of different perspectives, a multi-head attention mechanism is built to extract influences of different types of neighbor nodes on target user node features and fuse the influences, and social attribute features are output; on the basis of the user trust relationship network diagram, utilizing an attention mechanism to fuse neighbor information of the nodes to form trust features of the user nodes; and in combination with the social attribute features and the trust features of the user nodes, performing multi-view feature fusion, and outputting a predicted trust relationship. The problems that a traditional trust evaluation method depends on a predefined model and is poor in universality, and an existing trust relation prediction scheme based on a graph neural network is difficult to obtain a trust relation graph and is poor in feature fusion effect are solved.

The invention discloses a computing power network dynamic trust evaluation and access control method based on a GRU-BiLSTM fusion model, and the method comprises the steps: capturing the behavior dependence characteristics of a user and a node in a short period through a GRU, and employing the BiLSTM to model a bidirectional time sequence evolution rule of a trust relation, thereby achieving the classification prediction of the credibility level of the user and the regression estimation of the credibility degree of the node, and achieving the access control of the network. On the basis, a four-level access strategy is designed in combination with a system real-time load and a trust volatility, adaptive optimization of access control is realized by dynamically adjusting an access threshold, joint prediction of a bidirectional trust relationship between a user and a node is realized, and a more accurate behavior basis is provided for an access decision; and secondly, a trust volatility index is introduced, and a dynamic closed-loop mechanism of trust evaluation-policy execution-volatility updating is constructed, so that the access control policy can be adaptive to evolution of trust situation, and intelligent and refined authority management is realized.

The invention discloses a trust evaluation method and system based on a heterogeneous graph neural network. The method comprises the following steps: acquiring multi-dimensional information in a social network; optimizing the initial trust relationship representation based on a soft selection mechanism and a meta-path mechanism; learning and processing trust node information based on the trust prediction model; and evaluating the trust representation of the social node based on a trust prediction model to obtain a trust evaluation result in the social network. Through a soft selection mechanism, the importance degree of the trust chain of any length can be obtained. Through reconstruction of the meta-path adjacency matrix in the heterogeneous graph neural network and rotation operation of the features, the accuracy and robustness of social network trust evaluation are improved.

The present invention relates to a system and method for enhancing the security of smart contracts within blockchain networks by utilizing a hardware secure enclave for monitoring and suspending contract activities in response to detected security breaches. The system establishes a trust relationship between the hardware secure enclave and the smart contract, providing the smart contract with a unique enclave signature to ensure secure communications. A modular data monitoring application within the enclave is configured to detect suspicious activities, while an attestation process ensures the integrity of the enclave's code. Upon detecting a security threat, the system initiates a pause function to suspend contract operations and mitigate potential damage. The invention further leverages blockchain relayer modules to witness and transmit contract activity, and consensus mechanisms such as Proof-of-Work (PoW) or Proof-of-Stake (PoS) for transaction verification. This method provides a scalable, secure solution for preventing attacks on smart contracts and safeguarding digital assets in decentralized applications.

The invention discloses a multi-dimensional dynamic trust evaluation method and system for a new energy power terminal, and the method comprises the steps: extracting the universal features of the terminal based on terminal log interaction data, extracting special knowledge evidence according to an equipment level perception layer and a network layer, and converting all features into 0-1 standardized values; when a terminal accesses for the first time, the static attribute of the terminal is complementarily collected, so that an initial trust baseline is established and an initial trust value is given; firstly, an IoT device interaction diagram is constructed, nodes are terminal devices, attributes are knowledge evidence vectors, edges are device direct interaction relations, and weights of the edges are defined by historical interaction quality; fusing the equipment knowledge evidence and the interaction relationship through a node2vec algorithm to generate a low-dimensional embedded vector; and finally, calculating the cosine similarity of the device vectors, multiplying the cosine similarity by the interaction frequency proportion to obtain the direct trust degree of the 0-1 interval, and quantifying the direct trust relationship between the devices. Performing trust evaluation on the message flow dimension; and historical interaction behavior trust evaluation and timeliness optimization.

In at least one example, a method includes establishing, by a sniffer provisioning server (SPS) of a first wireless device, a trusted relationship between the first wireless device and a sniffer tool using a public key of the sniffer tool. An out-of-band (OOB) key exchange provisions the public key of the sniffer tool to the wireless device. The method further includes obtaining, by the SPS, key material uniquely related to a communication session established between the first wireless device and a second wireless device using a shared password. The key material excludes the shared password and a session key uniquely related to the communication session. The method further includes publishing, by the SPS, the key material over a channel to the sniffer tool based on the trusted relationship. The channel is secured using the public key of the sniffer tool.

The invention discloses a method for establishing a trust relationship between devices and an electronic device. Belongs to the technical field of communication. The method comprises the following steps: under the condition that a first device logs in an account and the first device is a first login device of the account, sending first device information of the first device to a server; a verification request for the second device is received, the verification request is sent to the first device by the second device through the server side under the condition that the second device logs in the account and it is determined that the first device information is stored in the server side, and the verification request comprises identity information of the second device; verifying the second equipment based on the identity information; and establishing a trust relationship with the second equipment under the condition that the verification of the second equipment is passed.

The invention discloses a computing power scheduling system and method for a computing power network, and relates to the technical field of computing power distribution scheduling, and the method comprises the steps: obtaining all computing power nodes in the computing power network, and constructing a computing power node interaction network model; obtaining a computing power task initiating node and computing power task attributes; determining a target attribute cluster of the computing power task based on the computing power task attributes, and recording all computing power nodes in the target attribute cluster as demand target nodes of the computing power task; based on the computing power task initiating node, determining an execution trust target node of the computing power task; solving an intersection of the demand target node of the computing power task and the execution trust target node of the computing power task, and recording the intersection as a comprehensive target node; and determining an execution computing power node of the computing power task from the comprehensive target node in combination with the balanced load. The method has the advantages that by constructing the interactive network model of the cooperative trust relationship and the attribute group clustering, multi-dimensional node dynamic screening and optimal matching are realized, and the efficiency and the reliability of computing power scheduling are remarkably improved.

The invention discloses a short message center information processing early warning method and system, and particularly relates to the technical field of information processing, and the method comprises the steps that a short message center receives short message content of a sending user, extracts sensitive vocabularies in short messages, determines similar short messages of the short messages of the sending user by using a similarity calculation method based on the sensitive vocabularies in the short messages, and sends the short messages to the sending user; determining short message behavior data of a sending user short message, determining a relationship between the sending user short message and a short message receiver through a knowledge graph, obtaining trust relationship data of the sending user short message, determining a risk short message, and determining the risk short message according to a historical record of sending the short message by the sending user and a record of sending the short message in a current monitoring time period. According to the method, the difference between the historical behavior and the current behavior of the sending user is determined through the KL divergence, the habit information of the sending user is determined, and the short message sending behavior of the sending user in the monitoring time period is warned in time, so that malicious short messages and junk short messages can be prevented from spreading, and the security of the platform is improved.

There is provided an apparatus comprising means for receiving, at an entity of a network from a user equipment, an indication of an identity associated with an avatar for use in an application function, wherein the user equipment is authenticated with the network and the application function has a trust relationship with the entity, determining, based on the identity associated with avatar, a digital signature and providing the digital signature to at least one of the user equipment and the application function for use in validating the avatar from the user equipment for use in the application function.