40 results about "Security privacy" patented technology

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.

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 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.

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.

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 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 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 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 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.

The invention provides a scheduling data security privacy enhancement method, device and equipment, and relates to the technical field of power system communication. The method comprises the following steps: encrypting local scheduling data by adopting a preset encryption algorithm to obtain first encrypted data; inputting the local scheduling data and the first encrypted data into a local neural network training model, and performing model training by taking the first encrypted data as a label and the local scheduling data as input to obtain a model gradient; and aggregating the model gradients by using a safety aggregator, obtaining a global gradient based on the aggregated model gradients, updating the local neural network training model established in each power station based on the global gradient, repeating the steps until a stop condition is reached, obtaining the updated local neural network training models, and obtaining the local neural network training models. And encrypting the corresponding local scheduling data. According to the method, the security privacy of the local scheduling data can be effectively guaranteed, so that the related data privacy leakage and security risk problems are avoided.

The methods and systems for improving communication distribution. In particular, the methods and systems for improving communication distribution in environments where there is both the need for end-user specific data (e.g., customized content) and / or data storage constraints. For example, in order to address the security / privacy concerns during communication distribution, the methods and systems use a novel architecture that limits the amount of data that must be stored. Specifically, the system does not require permanent storage of communications featuring end-user specific data prior to the distribution of these communications. Accordingly, the storage requirements are greatly diminished, and privacy / security concerns are avoided.

This invention discloses a blockchain-based attribute-based searchable encrypted data sharing method, comprising the following steps: Each data owner D i The system calculates its own public parameters and master key, and aggregates these public parameters to generate system public parameters. The data owner generates their own aggregated private key based on each data user's (DU) attribute set. The data owner encrypts their private data file using a symmetric encryption algorithm. A secure search index is constructed. Data users generate search trapdoors. A smart contract searches the trapdoors and the secure searchable index, verifying the access control policies of the trapdoors and the ciphertext keyword index, and checking if the keywords match. The data user decrypts the data to obtain the secure private data file. This invention allows each data user to maintain only one private key, using a single trapdoor for each search, offering advantages such as high efficiency, tamper resistance, low local storage overhead, fine-grained access control, and privacy protection.

The invention provides a smart home service system based on an Android platform, and belongs to the technical field of home service systems. Comprising a main control system module, a user interface module, an equipment control module, an automatic scene setting module, a security privacy protection module, an energy management module and a voice module, the main control system module comprises a core processor, an operating system and a communication module, the main control system module comprises a core processor, an operating system, a communication module, an operating system and an operating system customized and developed based on an Android platform, support for intelligent home equipment is optimized, an API interface and the communication module are provided, and multiple communication protocols such as Wi-Fi, Bluetooth and Zigbee are integrated; and stable connection with various intelligent devices is ensured, which is a brain of a smart home. According to the method, the user can reasonably arrange power utilization according to the prediction result, make energy planning in advance, avoid energy waste, and select to use the high-power electric appliance in the valley period according to the predicted energy consumption peak period, so that the power utilization cost is reduced.

The application discloses a kind of based on blockchain's traffic data security encryption and circulation system and method, belong to traffic control technical field, to solve the security, privacy and trust problem in traffic data sharing.System includes: the edge computing node near data source is deployed, and original traffic data is encrypted or privacy enhanced processing;Blockchain network with smart contract is deployed, manages node identity, records verification information, stores access strategy and controls data circulation;Data processing unit, aggregate processed data to generate circulatable data product.The method includes edge security processing, blockchain management verification, data processing unit product generation and blockchain according to strategy control circulation.The application guarantees data security privacy through edge security processing and blockchain trust mechanism, realizes the circulation and utilization of traffic data security, transparent and credible, and provides reliable data support for intelligent upgrading and digital transformation of traffic industry.

This invention discloses a method for generating Cypher query statements for graph databases based on thought chains, belonging to the field of graph database query technology. It includes data preprocessing, model training and query generation, model evaluation, security and privacy protection, system integration, and dynamic adaptive adjustment, transforming user natural language query requirements into executable Cypher query statements for graph databases. By defining meta-functions, the query problem is decomposed into combinations of basic operations, simulating the human thought chain and conforming to human logical problem-solving habits. This decomposition method makes the problem-solving process clearer, more organized, easier to understand and control. Whether it's developers constructing query logic or subsequent system maintenance and optimization, this intuitive problem decomposition method makes it more efficient and convenient.

This invention discloses a big data privacy protection intelligent collaboration system, relating to the field of data security and privacy technology. It includes: a privacy budget management module, which maintains a privacy budget pool, calculates data sensitivity levels, and allocates initial privacy budget quotas; a privacy budget monitoring module, which collects privacy budget consumption rates and usage rates; a full-process privacy audit module, which performs compliance checks and privacy impact assessments throughout the data lifecycle; a privacy risk assessment module, which calculates privacy risk scores using a structured feature weighted scoring method and generates risk warning information by combining context-aware analysis and an adaptive threshold adjustment mechanism; and a privacy budget scheduling module, which dynamically adjusts the privacy budget allocation strategy based on budget adjustment rules and constraint optimization algorithms, according to risk warning information, and processes the remaining budget according to budget redistribution rules when the task terminates. This invention achieves dynamic intelligent scheduling and closed-loop risk management of the privacy budget.

The invention relates to the technical field of industrial internet positioning and security privacy, and provides an industrial internet security cooperation positioning method and related equipment. The method comprises the steps that 1, an industrial internet platform issues a cooperative positioning task, and anchor nodes participating in the cooperative positioning task measure a target node to calculate position updating information of the anchor nodes to the target node; 2, performing security assessment on the anchor nodes participating in cooperative positioning according to node vulnerability levels and historical cooperative records, and selecting a security node set; 3, setting privacy noise and zero sum noise by anchor nodes in the security node set according to a privacy formulating protection level, combining the privacy noise and zero sum noise with the position updating information, and sending the position updating information to the target node; and step 4, after the target node receives the information with the privacy noise and the zero sum noise sent by the anchor node, calculating final positioning information based on the received information.

The invention discloses a vehicle and road cloud mass data security management method and system based on distributed storage, and relates to the technical field of data security. The method comprises the steps that an access road side and a vehicle-mounted terminal collect multi-source data and identify types, and a data set is generated; carrying out distributed addressing, determining node mapping, and distributing and constructing a storage cluster; performing hierarchical encryption on the storage cluster to generate a first encrypted fragment; the access request is analyzed, multi-node parallel verification is carried out on the first encryption fragment, and a second encryption fragment is read; and verifying the second encryption fragment and dynamically adjusting node mapping, and generating a data optimization management scheme. The technical problem that efficient expansion, security privacy protection and storage cost optimization of mass data are difficult to consider in existing vehicle and road cloud data storage is solved, high availability and elastic expansion of data distributed storage are realized, and the purposes of ensuring full-life-cycle security of the data through hierarchical encryption and improving the safety of the vehicle and road cloud data are achieved. And data distribution is dynamically optimized based on access verification, so that the storage cost is reduced, and the access efficiency is improved.

The invention discloses a data security protection method and system based on biological feature encryption and a storage medium, and relates to the technical field of data security and privacy protection.The data security protection method comprises the steps that a complete closed loop of end-side collection, local processing and comparison is constructed, and firstly, biological features are extracted on terminal equipment through a lightweight deep learning model; the key is converted into a stable endogenous key by adopting a fuzzy extraction technology; generating an irreversible and revocable template by applying isolated salting hash, and immediately clearing original data; and finally, through local comparison and a security sharing protocol based on zero-knowledge proof, the availability and invisibility of the biological characteristic data in the identity authentication process are realized, the data leakage risk caused by traditional centralized storage is fundamentally solved, the association tracking and abuse of the biological characteristics are effectively prevented, and the safety of the identity authentication process is improved. The authentication convenience is improved, and meanwhile, user-centered security privacy protection is realized.

The application discloses a lupus medicine reminding and compliance analysis system, relates to the technical field of lupus patient medicine health management, covers a multi-source heterogeneous data acquisition module, collects multi-element data by means of a cross-platform architecture and self-adaptive sensing, a dynamic intelligent medicine reminding module uses reinforcement learning and fuzzy logic to customize reminders, a precise compliance analysis module uses multidimensional algorithm evaluation, and there are deep data analysis and feedback, social interaction assistance, and a multi-level security privacy module, and the modules work cooperatively. The application can intelligently remind medicine taking, precisely analyze compliance, deeply mine data to help doctors adjust schemes, promote patient communication by means of social support, conveniently collects and transmits data by means of a watch terminal, and comprehensively helps lupus patient management, medicine taking and health.

The invention relates to the technical field of medical data processing, in particular to a nephropathy patient health record intelligent retrieval system which comprises a data acquisition and preprocessing unit, an ASIC special computing power unit, a high-speed retrieval and storage unit and a safety privacy management and control unit. According to an ASIC parallel computing architecture and a native homomorphic encryption circuit, nephropathy long-time-sequence feature extraction and pathological attention reasoning are efficiently completed on the premise that a ciphertext is not decrypted, a ciphertext high-dimensional feature vector and a plaintext pathological attention weight are accurately output, and based on the weight and the vector, the pathology attention of the plaintext is calculated. A nephropathy semantic quantizer generates a specific hash code retaining nephropathy pathology semantics and constructs an efficient inverted index to realize rapid accurate matching and fuzzy search of nephropathy health archives, so that privacy security of nephropathy medical data and accuracy of feature mining are ensured; and the file retrieval efficiency and the pathological semantic matching degree are greatly improved.

The invention provides a physical therapy agent inference engine design method based on multi-task learning. The physical therapy agent inference engine design method specifically comprises the following steps: constructing a multi-task learning model architecture; a dynamic parameter sharing mechanism application step; a privacy protection technology integration step; and a model training and optimizing step. According to the method, challenges of a medical AI inference engine in four dimensions of efficiency, safety, privacy and compliance are systematically solved, the balance of multi-task coordination and performance improvement is realized, the decision-making efficiency and accuracy are remarkably improved, resource waste caused by independent modeling for each task is avoided, a model can learn complementary information from associated tasks, and the efficiency of the medical AI inference engine is improved. And the generalization ability and the decision accuracy of the model are obviously improved.

The present application relates to the technical field of image processing, and particularly relates to a kind of image data desensitization method, device and equipment, the method comprises: extracting RAW domain image of image to be processed or video stream to be processed;First processing image is obtained by sequentially carrying out wide dynamic range processing, first bayer noise processing and tone mapping processing to RAW domain image;Dynamic ROI detection model and privacy classification model are acquired;Based on first processing image and dynamic ROI detection model, second processing image is output, and second processing image is labeled privacy area on first processing image;Based on second processing image and privacy classification model, the privacy level comprehensive score of each privacy area is obtained;Based on the privacy level comprehensive score of each privacy area, corresponding desensitization means is determined to carry out pixel-level privacy processing to second processing image, by processing the RAW domain image of video or image, end-to-end security privacy protection is realized.