71 results about "Security privacy" patented technology

A scalable platform for orchestrating networks of specialized AI multi-agent networks that enables secure collaboration through token-based protocols and real-time result streaming with advanced dynamic chain-of-thought pruning. The central orchestration engine manages domain-specific agents, implementing sophisticated multi-branch reasoning with contribution-estimation layers that evaluate each agent's utility using Shapley value-inspired metrics. The system employs information-theoretic and gradient-based surprise metric to guide memory updates and dynamic reasoning expansion, preventing local minima stagnation while preserving valuable insights through adaptive forgetting mechanisms. The platform unifies Monte Carlo tree search with contribution-aware estimation to detect high-synergy expert combinations while maintaining privacy through partial data approaches. It scales across distributed computing environments, enabling complex collaborative tasks like materials discovery, product engineering and manufacturing process design, biomedical research, and drug development. The system supports multi-party economic rewards through systematic contribution effort, cost and importance tracking, while standardized interfaces manage security, privacy, and policy constraints across heterogeneous agents.

A platform for coordinating networks of specialized AI agents that enables secure collaboration through token-based communication and real-time result streaming. The system features a central orchestration engine managing interactions between domain-specific expert agents, with memory management and optional encryption for secure data handling. The platform uses efficient communication protocols for knowledge compression and faster reasoning, while a standardized agent interface system handles security, privacy, and policy requirements. It scales across distributed computing environments to enable complex collaborative tasks like personalized content creation, materials discovery, and drug development while optimizing resource usage and maintaining data privacy.

The invention discloses a big data privacy protection modeling method and system based on federated learning and a block chain, and relates to the technical field of privacy protection and joint modeling. According to the method, homomorphic encryption, differential privacy, federated learning, secure multi-party computing and block chain technologies are fused, big data privacy protection and joint modeling are realized, encryption and dimensionality reduction are performed on original data through homomorphic encryption and differential privacy, an encrypted training sample of secure privacy is generated, a local model is trained on an encrypted data set through federated learning, and a big data privacy protection result is obtained. The method comprises the following steps: calculating aggregation parameters by using security multiple parties, constructing a verification network in combination with a block chain, ensuring credibility and integrity of model training, and finally, adding noise optimization performance for a global model by using differential privacy, testing generalization ability through cross validation, and determining a deployable privacy protection joint learning model, thereby breaking traditional data islands, promoting cross-mechanism data cooperation, and improving the privacy protection performance. Big data values are released, and data protection regulations and privacy requirements are met.

The invention discloses an identity authentication and control method and device based on a block chain. According to the method, biological features are collected through edge nodes to generate feature vectors, a combined hash value is generated in combination with a device scene label and a service role label, the combined hash value is uploaded to a cloud server after encrypted signature, and the combined hash value is written into a block chain through an intelligent contract; and during user authentication, the edge node calculates a real-time risk level, dynamically selects an authentication mode, calls an intelligent contract for verification after verification of the cloud server, and adjusts the risk level according to a verification result to implement management and control. According to the method, the edge cloud collaborative architecture is adopted, and the dynamic multi-factor authentication mechanism and the block chain consensus technology are combined, so that high-security privacy protection authentication is realized, the security requirements of different service scenes can be met, data leakage and replay attacks are effectively prevented, and the authentication efficiency and reliability are improved.

The invention discloses a traffic data security encryption and circulation system and method based on a block chain, belongs to the technical field of traffic control, and aims to solve the problems of security, privacy and trust in traffic data sharing. The system comprises an edge computing node which is deployed near a data source and is used for performing encryption or privacy enhancement processing on original traffic data; a block chain network with a smart contract is deployed, node identities are managed, verification information is recorded, an access strategy is stored, and data circulation is controlled; and the data processing unit is used for aggregating the processed data to generate a circulatory data product. The method comprises the steps of edge security processing, block chain management verification, product generation by the data processing unit and management and control circulation of the block chain according to a strategy. Through edge security processing and a block chain trust mechanism, data security privacy is guaranteed, safe, transparent and credible circulation and utilization of traffic data are realized, and reliable data support is provided for intelligent upgrading and digital transformation of the traffic industry.

The invention belongs to the technical field of electronic document processing, and particularly relates to an electronic document standardization modeling processing system which comprises a document input preprocessing module, a format standardization conversion module, an analysis reconstruction module, a metadata extraction management module, a quality inspection correction module, an experience optimization module and a security privacy protection module. According to the application, the acceptability of documents of different sources is improved through the document input preprocessing module, it is ensured that various types of electronic documents can be processed, the problem of typesetting disorder caused by format differences is reduced through the format standardization conversion module, and the document appearance consistency is kept through accurate style mapping; the analysis precision is improved through the analysis and reconstruction module, so that the original layout and style are better reserved; through the metadata extraction management module, the document management and retrieval capability is enhanced, and meanwhile, an adjustment space is provided to adapt to requirements under special conditions.

The invention discloses a thinking chain-based graph database Cypher query statement generation method, and relates to the technical field of graph database query. Comprising the steps of data preprocessing, model training and query generation, model evaluation, security privacy guarantee, system integration and dynamic adaptability adjustment, and a natural language query requirement of a user is converted into a Cypher query statement executable by a graph database. By defining a meta function, a query problem is decomposed into a combination of basic operations, a human thinking chain mode is simulated, and the logic habit of human to process the problem is met. By means of the decomposition mode, the problem processing process is clearer, more organized and easy to understand and master. The construction of the query logic by developers and the subsequent maintenance and optimization of the system become more efficient and convenient due to the visual problem decomposition mode.

The invention belongs to the technical field of block chains and information security, and particularly relates to a cross-domain access method for enhancing security privacy protection based on a block chain. The architecture comprises a global coordination chain and a plurality of domain alliance chains; the global coordination chain deploys a strategy Merkel tree root, a cross-domain authentication log and an SGX security area verification record to form a global credible verification anchor point; the domain alliance chain adopts a distributed autonomous mode, equipment registration information is maintained in each independent domain, a policy tree and an anonymous certificate library are dynamically accessed, and data sovereignty isolation is realized. The invention aims to solve the problems of identity authentication centralization, easy leakage of privacy data, low cross-domain trust transmission efficiency and the like in the traditional cross-domain access technology.

This disclosure provides techniques to utilize decentralized identifiers (DIDs) and verifiable credentials for secure, privacy-preserving transactions. In one aspect, a method is provided that includes: receiving user information; determining a DID based on the information; providing the DID to a user device; verifying the user's identity by validating the DID and associated verifiable credentials; and performing a transaction based on the verified DID. Other aspects are provided, such as generating a public-private key pair for the user, associating the DID with the public key, and / or creating a DID document stored on a distributed ledger accessible to authorized entities. Further aspects include processing transactions through smart contracts on a blockchain network, which may involve converting central bank digital currency to fiat currency while maintaining user privacy, applying transaction limits based on verified identity attributes, and providing zero-knowledge proofs to auditors to verify compliance without accessing underlying transaction details.

The invention relates to the technical field of image processing, in particular to an image data desensitization method, device and equipment, and the method comprises the steps: extracting a to-be-processed image or a RAW domain image of a to-be-processed video stream; sequentially performing wide dynamic range processing, first Bayer noise processing and tone mapping processing on the RAW domain image to obtain a first processed image; obtaining a dynamic ROI detection model and a privacy grading model; based on the first processing image and the dynamic ROI detection model, a second processing image is output, and the second processing image is that a privacy area is marked on the first processing image; based on the second processing image and a privacy grading model, obtaining a privacy level comprehensive score of each privacy area; and determining a corresponding desensitization means based on the privacy level comprehensive score of each privacy area so as to carry out pixel level privacy processing on the second processing image, and realizing end-to-end security privacy protection by processing the RAW domain image of the video or the image.

The invention discloses an Internet of Things industry intelligent customer service supervision and control system based on artificial intelligence, and belongs to the technical field of customer service supervision. Comprising an omni-channel intelligent access and intention understanding module, an AI intelligent center and complex decision module, an intelligent supervision and ethical regulation and control module, a man-machine cooperation and humanistic care module, a data-driven optimization and edge intelligent module and a security privacy and controllable treatment module, and the omni-channel intelligent access and intention understanding module is used for integrating multiple channels. Unified request distribution is achieved, data input by a user are analyzed through voice recognition, NLU natural language understanding and image recognition technologies, composite intentions are accurately captured, interaction strategies are dynamically adjusted in combination with device state data, user historical behaviors and real-time positions, and pacified talking skills or manual intervention are triggered through voiceprint / text emotion analysis. On the basis of realizing customer service supervision and regulation, all-channel fusion and intention accurate analysis can be realized, and ethical safety integrated design can be realized.

In order to meet hierarchical, multi-user and differentiated application requirements in a complex environment, the invention provides an image grading security privacy protection method, which comprises the following steps of: partitioning a plaintext image to be encrypted, classifying DCT (Discrete Cosine Transform) coefficients of image blocks, and carrying out non-uniform compression by utilizing a compressed sensing technology; and in combination with adaptive threshold sparsification and a scrambling-diffusion encryption method, progressive image grading security privacy protection oriented to users with different grades of permissions is realized. Wherein the user with the low-level authority can only obtain the edge contour information of the image, the user with the middle-level authority can obtain the image with fuzzy texture details, and the user with the high-level authority can obtain the image which contains contour and detail information and has the best visual effect, so that hierarchical access control is realized.

The present invention discloses a strong security ciphertext retrieval method and system that supports result pattern leakage hiding, comprising two parts: a subset predicate encryption method capable of hiding vectors and a strong security ciphertext retrieval method capable of hiding result pattern leakage hiding. The said subset predicate encryption method capable of hiding vectors implements a strong security privacy discrimination method for vector subsets, by performing a one-time encryption and request process on the vector subset, thereby judging whether the predicate set belongs to the original overall attribute set, and will not leak relevant privacy information. The said strong security ciphertext retrieval method capable of hiding result pattern leakage hiding solves the privacy leakage problem in the member detection and matching process in the traditional connection keyword searchable encryption scheme, by performing member existence discrimination on the label set of the keyword document pair, and in this process, the result pattern association information between the keyword and the document will not be leaked, thereby effectively enhancing the security of the system.

The invention discloses an illegal evidence chain evidence obtaining method and system based on external graphic features of a garbage bag, and relates to the technical field of garbage classification, and the method comprises the steps: obtaining an illegal putting graph uploaded by an inspection worker; inputting the violation putting image into a target identification model, and obtaining a violation image label; and screening out target video data from a video database according to the illegal image tag, and storing the target video data as law enforcement evidence. According to the invention, the efficiency and accuracy of garbage classification and illegal behavior supervision can be improved, the security, privacy and authenticity of data are ensured, a favorable means based on illegal evidence is provided for supervision of unclassified residents, and conditions are provided for unattended delivery points.

The present invention discloses an automatic audit and inspection method and system based on emission source statistical data, which relates to the technical field of statistical data auditing. The method first collects data through multimodal fusion and then pre-processes it through adaptive noise filtering and data enhancement. Fuzzy logic and genetic algorithms are used to dynamically generate optimization rules, and automatic auditing is carried out with the help of deep convolution and long short-term memory networks. Anomalies are detected and graded warnings are issued, and intelligent correction suggestions are provided. The results are stored in multiple dimensions and visually fed back. The method also covers security, privacy, and external collaboration steps. The present invention improves the efficiency and accuracy of emission source statistical data auditing through multimodal acquisition, intelligent auditing, and other technologies. It can dynamically optimize rules, provide graded warnings, and intelligently correct them. It has security protection and external collaboration functions, providing strong support for environmental management decisions.

This application provides a data processing method, apparatus, and related equipment based on a blockchain network. The method includes: a first node sending an access request for target data to a second node of a second business sub-chain, the access request carrying verification information of a first block of the first business sub-chain, the first block storing a pre-access record of the target data by the first node; receiving first response data sent by the second node, the first response data including authorized access information of the target data and identification information of the Trusted Execution Environment (TEE) of a third node; sending a request to obtain the target data to the third node according to the identification information of the third node's TEE, and receiving encrypted target data generated by the third node's TEE sent by the third node. This method can achieve efficient data sharing between multiple chains and ensure security and privacy during cross-chain data interaction, thereby improving the operating efficiency and security of the blockchain network.

The invention provides a data sharing method and device and a computer program product, and aims to realize safety, privacy protection and efficient sharing of data, and the method comprises the following steps: a trusted authorization center generates a homomorphic encryption public and private key pair for a data provider; the data provider performs homomorphic encryption on the original data by using the public key and then uploads the original data to the IPFS cluster, and the cluster calculates a data hash address and generates a data fingerprint; and the data provider sets an access control strategy, performs attribute encryption on the data fingerprint, and uploads a result to the data sharing block chain. And when a data visitor requests for access, the block chain verifies the matching between the attribute of the data visitor and the access control strategy, and if the matching is successful, the visitor is allowed to obtain the encrypted data and decrypt the encrypted data by using the corresponding private key, and finally original plaintext data is obtained. According to the method, data privacy and security are effectively protected, and flexible data sharing is realized at the same time.

The application relates to a mobile hard disk encryption method based on a touch screen and a mobile hard disk, and the mobile hard disk encryption method comprises the following steps: S1, generating encryption track data through a touch screen module; S2, converting the encryption track data into encryption instructions, and converting a register into a register in an encryption state according to the encryption instructions; and S3, triggering decryption instructions in the mobile hard disk in the encryption state, and updating the register in the encryption state into a decryption state according to the decryption instructions. In the prior art, the data security problem is that people with ulterior motives can easily steal the mobile hard disk or steal the data of the hard disk in a short time; the scheme can solve the problems that the password operation of the mobile hard disk is complicated and the state display is not intuitive while the safety and privacy are considered.

The invention discloses an industrial data sharing method and system based on cognitive intelligence and a storage medium, and the method comprises the steps: constructing an evolutionary deep learning identity verification system, and achieving the dynamic identity verification and behavior anomaly detection of heterogeneous equipment through a genetic algorithm, online incremental learning and multi-model integrated voting. In the factory, a space-time attention mechanism is combined with a dynamic graph neural network, data core features are extracted through self-supervised comparative learning, and equipment time sequence dependence, space correlation and topology dynamic changes are captured; a scheduling strategy is constructed through multi-agent deep reinforcement learning, a game theory balancing mechanism is introduced, edge nodes are coordinated to process high real-time requirements, and disaster recovery is optimized; generating unique identifiers of equipment, nodes and features; the cognitive intelligent decision engine analyzes the features, generates optimization suggestions in combination with a knowledge graph and causal reasoning, triggers an alarm in case of abnormality, and performs closed-loop response through an automatic control loop. According to the invention, the intelligence, reliability and security privacy protection capability of the system are improved.

The invention discloses an automatic auditing and checking method and system based on emission source statistical data, and relates to the technical field of statistical data auditing. The method comprises the following steps: acquiring data through multi-modal fusion, and carrying out adaptive noise filtering and data enhancement preprocessing; an optimization rule is dynamically generated by applying fuzzy logic and a genetic algorithm, and automatic auditing is performed by means of deep convolution and a long-short term memory network; and when abnormal conditions are found, grading early warning is carried out, intelligent correction suggestions are provided, results are stored in a multi-dimensional manner and are visually fed back, and security privacy and external collaboration steps are covered. Through the technologies of multi-mode collection, intelligent auditing and the like, the auditing efficiency and accuracy of the statistical data of the emission source are improved, rules can be dynamically optimized, graded early warning and intelligent correction can be achieved, the safety guarantee and external cooperation functions are achieved, and powerful support is provided for environmental protection management decisions.

The invention discloses a multi-source data view feature extraction and quick matching system based on deep learning, and relates to the technical field of computer deep learning, a multi-modal data preprocessing module supports access of various heterogeneous data, technologies such as adaptive normalization are adopted to process data, a feature extraction module constructs a multi-branch attention network architecture, and a multi-source data view feature extraction and quick matching system is established. The trunk uses improved ResNet50 and introduces a channel attention mechanism, output of each branch generates a joint feature through a tensor fusion layer, the matching retrieval module adopts a layered hash coding strategy and a multi-index hash table, the weight learning module dynamically adjusts modal weight through a meta-learning framework and a context awareness mechanism, and the matching retrieval module performs matching retrieval on the modal weight through the meta-learning framework and the context awareness mechanism. The semantic enhancement module constructs a knowledge graph embedding layer and develops a semantic similarity calculation function. The multi-branch attention network improves the accuracy of feature extraction, distributed computing acceleration supports high-concurrency processing, and the method also has the functions of incremental learning, interpretable analysis and security privacy protection, and meets various requirements.

The invention relates to a mobile hard disk encryption method based on a touch screen and a mobile hard disk. The mobile hard disk encryption method comprises the following steps: S1, generating encryption track data through a touch screen module; s2, converting the encryption track data into an encryption instruction, and converting a register into a register in an encryption state according to the encryption instruction; and S3, triggering a decryption instruction in the mobile hard disk in the encryption state, and updating the register in the encryption state into a decryption state according to the decryption instruction. In the prior art, the problem of data security is solved, and a mobile hard disk is easily stolen by a person with an exclusive mood or the data of the hard disk is stolen in a short time; according to the scheme, the problems that password operation of the mobile hard disk is tedious and state display is not visual can be solved while security privacy is considered.

The invention particularly relates to a system and method that is used artificial intelligence, distributed computing, energy efficiency, optimization, cybersecurity, privacy field and relates to a decentralized system that not only optimizes neural networks for devices with varying capacities but also provides a robust defense mechanism against cybersecurity and privacy threats.

The invention discloses an anti-quantum traceable anonymous authentication method and system for a mobile internet of things, and belongs to the technical field of identity authentication and tracking. The method comprises an initialization stage, a mobile Internet of Things equipment registration stage, a mobile Internet of Things equipment authentication stage and a mobile Internet of Things equipment tracking and revocation stage. Bidirectional authentication and session key negotiation between an edge node and equipment are realized by utilizing a lattice-based chameleon hash and a short integer solution problem, quantum computing attacks are resisted, and meanwhile, the equipment identity and path privacy are protected through block chain evidence storage and a chameleon hash trap door technology, and the security of the equipment is improved. And on-demand accurate tracing and rapid revocation of malicious equipment by a law enforcement agency can be supported, and the requirements of safety, privacy and supervision in a mobile Internet of Things scene are met.

The application relates to the technical field of scene linkage control, and discloses an intelligent scene linkage control platform and equipment, which comprises an environment monitoring model and a user behavior analysis model, wherein the environment monitoring model is used for predicting environmental changes, the user behavior analysis model is used for identifying a scene and predicting user behavior through target detection data, a user interface module comprises a user interface, a feedback unit, a scene management unit, an intelligent recommendation unit, a monitoring and maintenance unit and a security and privacy unit, and a fault detection module realizes fault detection of the intelligent scene linkage control platform through a fault model, so that the complexity of user configuration is reduced, the system usability is improved, and all types of faults that are difficult to identify are greatly reduced, thereby causing missed reports or false reports.

Systems and methods for uses and / or improvements to blockchain and blockchain technology, particularly to provide a scalable solution to the aforementioned security and privacy concerns. As one example, systems and methods are described herein for a double-layer restriction subnet architecture that overcomes the technical limitations of conventional blockchains, whether public or permissioned, and subnets thereof. The double-layer restriction subnet architecture comprises a series of permissioned subnets, which provides both the security / privacy benefits of permissioned blockchains but also the scalability of subnet efficiency.

The invention provides an image display method, a traceability method, a processing method, a device and a system, and belongs to the technical field of computers. A sensitive area in an original image is obtained, a watermark is embedded in the original image for the sensitive area to obtain a watermark image, and finally the watermark image is displayed. The sensitive area is an area where sensitive information in the original image is located, and the sensitive information is information with security privacy protection requirements in the original image. The area proportion of the watermark in the watermark image in the sensitive area is greater than or equal to a proportion threshold value. The watermark is embedded in the original image for the sensitive area in the original image, so that the sensitive area is fully covered by the watermark, the watermark can be effectively extracted from the sensitive area after sensitive information is leaked due to the fact that the sensitive area in the watermark image is secretly recorded or screenshot, the leakage source can be traced, and the watermark traceability reliability is improved.

The invention discloses a vaccination behavior intervention system and method, and belongs to the technical field of vaccination management. The system comprises a security and privacy module, a user health file module, a personalized behavior intervention module, an NLP module, a data acquisition and analysis module, a real-time feedback module and the like, security and privacy are guaranteed by setting login authority and encrypting user information, a personalized intervention plan is made by using the user health file, a user language is processed to obtain an inoculation intention, and an inoculation information generation report is analyzed. And further adjusting the intervention plan and carrying out reminding and follow-up. Compared with a traditional intervention means, the vaccination method can overcome the limitation that the information spreading speed is low, and accuracy and individuation are insufficient, individual vaccination behaviors are intervened and guided in real time through an intelligent means, the vaccination rate of the public can be increased, and public health challenges can be coped with.

The present invention relates to an intelligent automobile anti-theft alarm device applied to the field of automobile anti-theft, including an anti-theft system installed in a vehicle and a car owner App connected to the anti-theft system through cloud technology, including a signal acquisition module for collecting data on the environment in which the vehicle is located to assist in determining whether the vehicle is in a stolen state; a privacy recording module for recording the security and privacy information of the vehicle; an anti-theft protection module; an alarm output module for providing alarm prompts and assisting in verifying the anti-theft state; and a patrol and inspection module. In the above-mentioned intelligent automobile anti-theft alarm device, this anti-theft system reduces the false alarm rate in complex environments such as downtown areas, and can cope with various attack methods at the same time. The modules are intelligently linked to form a comprehensive protection system, which ensures both safety and ease of use.

The application discloses an application anomaly detection method and device, equipment and a readable storage medium, and related embodiments can be applied to the fields of data security, application security, applet security, cloud security, privacy protection and the like. The method comprises the following steps: constructing a target node structure tree of an application to be detected, which comprises an interactive component and an extended description text; performing word segmentation processing on a target description short text in the target node structure tree to obtain a target description word segmentation; performing similarity matching on the target description word segmentation and word segmentation in a detection information dictionary to determine a detection information type of the target description word segmentation; and determining a detection result according to an event type of an event trigger attribute and the detection information type. By using the application, the cost and time consumption of anomaly detection on the application to be detected can be reduced.