6448 results about "Encryption" patented technology

The invention discloses a power system source network interaction data security encryption verification method, system, device and medium, and belongs to the technical field of power system communication encryption, and the method comprises the following steps: a source side device and a network side device complete identity authentication through a bidirectional digital certificate verification mechanism; and an identity binding label is generated in combination with the device identifier, the timestamp and the position information. And after the authentication is passed, the two parties perform key negotiation based on an elliptic curve algorithm, and generate a temporary encryption key in combination with an authentication result. A source side device carries out structural packaging on original interaction data, adds a random number, a timestamp and a hash abstract, then encrypts the original interaction data in an AES-GCM mode, and carries out signature binding on key fields through digital signatures to form a complete data packet. And a receiving end performs compliance judgment on the timestamp and the random number in the data packet, and after the timestamp and the random number are confirmed to be in an effective time window and are not replayed, signature verification, decryption processing and Hash consistency verification are sequentially completed, so that closed-loop processing of a data flow is ensured.

The invention relates to a data security processing method and system based on distributed storage, and relates to the technical field of computer information processing. The method comprises the following steps: cutting data into encryption fragments with a configurable number by adopting a dynamic fragmentation strategy, and generating a physically isolated dynamic check block in combination with a timestamp to realize tampering prevention; a dynamic threshold value is dynamically calculated based on the data sensitivity index and the node load, and the node is optimized through the reliability score for cooperative decryption; a database table is divided into independent marshalling storage according to main foreign key association, foreign key fields are encrypted by adopting cross keys, and cross-marshalling access needs to meet a multi-key threshold condition; an intelligent threat perception engine is constructed, access logs and threat intelligence are analyzed in real time, and key rotation, fragment replacement and joint defense response mechanisms are dynamically triggered. According to the invention, full life cycle protection of data is realized, and the problems of key leakage risk and cross-table association attack are effectively solved.

A method is provided for dynamically generating a digital watermark for a data file. The method includes receiving a request to access the data file from a user; dynamically generating an encryption key based on at least one parameter selected from the group consisting of the identity of the user, the time of access, and the mode of access; embedding a digital watermark into the data file using the dynamically generated encryption key, wherein the digital watermark is unique to the request; providing access to the data file with the embedded digital watermark to the user; and storing information related to the encryption key and the parameters used for its generation in a secure database.

Systems and methods for large language model (LLM)-agnostic data anonymization. Data anonymization includes data obfuscation (and data deobfuscation) to protect confidential information a user is going to send to an LLM service or application programming interface (API). Encryption can be used for data obfuscation and particularly, for securing data from unauthorized access. Likewise, decryption can be used for data de-obfuscation.

The invention relates to the technical field of edge calculation application and partial discharge detection, in particular to a partial discharge multichannel signal real-time synchronous acquisition method based on edge calculation. According to the method, the functions of multi-channel signal acquisition, time synchronization, feature analysis, hierarchical storage and the like are integrated at edge nodes, asynchronous acquisition, unified timestamp marking and data synchronous fusion of multiple types of partial discharge signals are realized, and extraction of multi-dimensional feature parameters such as time domain, frequency domain and energy and intelligent event discrimination are locally completed. For abnormal signals, the system realizes classified storage and remote uploading after encryption and compression processing; and for normal signals, dynamic management is carried out through circular caching. According to the method, the accuracy and efficiency of multichannel signal synchronous acquisition are remarkably improved, the data safety and the system adaptive capacity are enhanced, and the method is suitable for real-time online monitoring and intelligent diagnosis of partial discharge of power equipment.

The invention discloses a cross-border data flow management and control system and method based on privacy calculation verification and a medium. The system comprises a legal knowledge graph construction module, a compliance strategy dynamic generation module, a privacy calculation sandbox module, a data flow topology analysis module and a full-link audit tracing module. Natural language terms are converted into programmable compliance rules through a legal knowledge graph, a technical system is driven to automatically adapt to policy changes, the whole process from single-point protection to full-link privacy calculation is achieved, namely, the whole process of data encryption transmission, secret state calculation and compliance verification is covered, global laws and regulations can be analyzed in real time, and an executable technical strategy can be generated; from sovereign confrontation to sovereign collaboration, a sovereign compliance map is constructed through digital twinning, and a data flow path is optimized. According to the method, digital watermark marking is carried out on all nodes of data flow, traceability and responsibility definition of leakage events can be realized, and a cross-border data flow space-time barrier is broken through.

The invention provides a block chain-based clinical test data integrity system, and relates to the technical field of data processing, and the system comprises the following components: a multi-source heterogeneous data acquisition and preprocessing module, a multi-level encryption and under-chain data storage module, an alliance block chain network, and an alliance block chain network maintenance and verification shared distributed account book. The distributed account book only stores all digitally signed clinical test data fingerprints, metadata and operation logs, does not store original data, and is linked with the intelligent contract automatic management module, so that the clinical test data cannot be tampered in the whole life cycle from the source to archiving. Hash anchoring, digital signature and decentralized verification mechanisms of the block chain technically eradicate the possibility of unauthorized tampering of data, and ensure scientificity and reliability of clinical test results.

The invention belongs to the field of civil aviation, provides a civil aircraft field service operation scheduling control system, and aims to solve the problem of low cooperative efficiency of multiple links of ground service scheduling. File management is based on an Ali cloud OSS development interface, supports multi-format files, and realizes functions of permission access, encryption and the like; communication adopts an MQ / MQTT architecture to construct an IM system, and supports multi-type message transmission and http network communication; data processing packages a multi-language database interface, and internal and external network secure intercommunication is realized through a gatekeeper agent. Flight functions cover and guarantee node management and control, dynamic updating, cross-department communication, real-time flight data butt joint, task distribution of unified operation according to work types, and support of multi-terminal such as a web terminal and a handheld terminal and nailing access. Ground service multi-scene requirements can be met, and the operation efficiency and the management level are improved.

The invention belongs to the technical field of block chains, and discloses a block chain-based digital identity authentication and traceability method, which comprises the following steps: acquiring user biological characteristic data, generating a characteristic root value, splitting key shares, and generating a key share set through block chain evidence storage; each distributed node generates an identity private key and an on-chain identity template, and associates the on-chain identity template with a chain identifier to form a multi-chain identity key pool and an on-chain identity template library; dividing a core chain and an edge chain, generating a zero-knowledge proof, generating a cross-chain certificate after verification of the core chain, sending an encryption result to the edge chain, and generating a temporary authority token; writing traceability information into the edge chain, aggregating multi-chain information through cross-chain traceability, and generating a traceability information chain and a cross-chain traceability validity proof; and recording a key use track and identifying a risk behavior, triggering a key limiting mechanism, dynamically updating an identity template permission on the chain, reversely optimizing key related parameters, and forming a closed-loop iterative identity and traceability management link.

The invention relates to the technical field of computer network security, and discloses a computer network security access control management method based on big data. The method comprises the following steps: constructing a network security situation knowledge graph, collecting a real-time access behavior sequence through a probe, and synchronizing the real-time access behavior sequence to the knowledge graph; simulating a network entity interaction state in the knowledge graph, and predicting a threat propagation path and a potential intrusion behavior; setting a dynamic access control strategy, constructing a multi-dimensional feature matrix in combination with a real-time access behavior sequence association influence degree and a strategy execution priority constraint condition, calculating a strategy conflict risk score by using a deep learning model, comparing with a preset threshold to judge whether a conflict exists or not, and if yes, reconstructing the strategy; and automatically executing access blocking, session termination and data encryption operations according to the reconstructed strategy, recording an execution log and security feedback data, and updating the knowledge graph in real time. According to the method, the dynamic property and the security of access control are improved, and security threats in a complex network environment can be effectively handled.

The invention discloses a server BMC dynamic security authentication and firmware protection method and system based on a hardware root of trust, relates to the technical field of server remote management security, and discloses the server BMC dynamic security authentication and firmware protection method and system based on the hardware root of trust, which realize dynamic authentication by generating a device fingerprint through a security chip. According to the method, a multi-layer protection mechanism is constructed in combination with fragment encryption, differential hash check and memory integrity verification, and meanwhile, the data credibility is enhanced by using a block chain storage key hash value, so that the problems of static authentication risk, insufficient firmware tampering detection and missing of a trust chain in a traditional scheme are effectively solved, and the security protection capability of a BMC system can be improved.

The invention relates to a prefabricated building quality defect tracing system and method applied to the field of building informatization, and the system comprises a user interaction layer, a data processing and storage layer, a data collection layer and a function layer, and the data collection layer is used for collecting key quality data of prefabricated building components in different links; the user interaction layers interact with each other through a network and the function module layer; the data processing and storage layer performs encryption, hash operation, scattered storage and index verification on the quality data transmitted by the data acquisition layer by using an intelligent contract, an IPFS network and a block chain; the function module layer provides support for each unit of the user interaction layer to trace quality defects, judge responsibility and take prevention measures, and the system can collect the quality data of the whole process of the prefabricated building, comprehensively manage the quality tracing process, strengthen multi-party collaboration and sharing, and improve the quality of the prefabricated building. And it is ensured that tracing of the quality defects of the fabricated building has comprehensiveness, transparency and non-tampering performance.

The invention provides a cloud platform docking service implementation method, system and device based on an adaptation layer and a medium, belongs to the technical field of cross-platform resource management and service integration, and particularly relates to a method for configuring an adapter for each cloud platform and mapping an API (Application Program Interface) of the platform to a standard RESTful API interface; performing standardization processing on interface return formats of different cloud platforms through a data conversion module, converting a heterogeneous format into a unified format, and outputting a unified data format; packaging and abstracting services of different cloud platforms; identity authentication is realized by randomly generating a secret key in cooperation with an encryption and decryption algorithm, and a verification mechanism of a source request IP is preset; and recording an operation log and an error log in the docking process, and recording an interface calling frequency, a requester IP and error information of an abnormal logic node. According to the method, the adaptation layer is introduced, the isomerism of the bottom cloud platform is shielded, and unified interfaces and services are provided, so that efficient and flexible cloud platform docking is realized.

The invention discloses an electronic archive intelligent retrieval method and system based on a block chain, and relates to the technical field of archive retrieval, and the method comprises the steps: extracting text features of an electronic archive, and generating metadata; generating a content hash value from the electronic file original text; writing the metadata, the content hash value and the ABE access strategy into the block chain smart contract; constructing a reverse index based on the metadata semantic tag, wherein an index entry is associated with a block chain storage address; calculating a root hash and anchoring the root hash to the block chain; analyzing a keyword and a digital identity certificate in the user retrieval request; calling an intelligent contract to verify whether the user attribute accords with the ABE access strategy of the target file; retrieving an encrypted hash list matched with the file in the distributed index; acquiring the encrypted file fragments from the distributed storage system; verifying data integrity; and combining the fragments to generate a final retrieval result. The method has the advantages that through deep coupling of the block chain and attribute encryption, an electronic archive management system considering security and intelligent retrieval is constructed.

The present invention relates to the technical field of network security protection. Disclosed are a security protection method and apparatus for a customer service management system. The method comprises: acquiring an employee data set, and performing permission assignment, so as to generate an employee operation permission set; performing identity verification on an access user, and determining a data management operation permission range of the access user; acquiring a sensitive data set for encryption processing, and storing same in a customer service management system; accessing data of the customer service management system, implementing an access control policy, and performing risk assessment, so as to generate a system risk level; extracting detected anomalous data, synchronizing same to a security protection network, and outputting a protection control policy; and executing the protection control policy for security assessment, regularly updating the protection control policy, and performing intelligent security protection on the customer service management system. The present invention solves the technical problem in the prior art that customer service management systems have low security protection capacity, which leads to difficulty in preventing network attacks, thus achieving the technical effect of improving the security protection capacity of customer service management systems.

The invention discloses a logistics order management system and method, and belongs to the technical field of logistics information management. The method comprises the following steps: step 1, generating a unique digital fingerprint for each logistics order; step 2, performing multi-level security encryption and state synchronization management on order information; 3, constructing a digital twinborn model corresponding to the order, collecting and preprocessing key data in real time and visually displaying the key data in the logistics process, and realizing dynamic monitoring of the whole process; step 4, based on an order state consensus mechanism, automatically matching optimal logistics resources and driving an order processing flow, and generating a verifiable order execution proof chain at the same time; and step 5, performing intelligent analysis and adaptive optimization on the full-life-cycle data of the order, and continuously improving the overall efficiency and precision of logistics management.

The invention relates to the technical field of data sharing security, in particular to a government affair data security sharing method and system based on a block chain technology. The method comprises the following steps: acquiring user service handling information, analyzing user service requirements according to the user service handling information, and determining target multi-level department chain information; according to the target multi-level department chain information, performing multi-level encryption anchoring uplink storage on the user service handling information, and determining service multi-level department chain information; and based on an intelligent contract driving strategy, according to the user service demand and the service multi-level department chain information, performing multi-department chain type cooperative processing on the user service demand, and determining and outputting a government affair processing result. According to the application, the data sharing security among different hierarchy departments in the government affair processing process is improved, good balance between data security and government affair processing is effectively guaranteed, the working efficiency and experience of users are improved, and the government affair electronization process and efficient configuration of social resources are promoted.

The invention relates to the technical field of Internet of Things data transmission, in particular to a mass data cross-security domain transmission high-low priority queue hierarchical scheduling method based on Internet of Things equipment, which comprises edge computing node classification, independent channel design, a dynamic weight distribution algorithm and a block chain encryption watermark technology. The timeliness is improved through a preemptive and compensation mechanism, and the reliability is enhanced in combination with queue degradation protection and a dynamic adjustment strategy. The method can effectively solve the problems that timeliness is insufficient and safety and efficiency are difficult to balance in a traditional method, the key data transmission efficiency and the system self-adaptive capacity are remarkably improved in a complex network environment, and the method has wide application prospects.

The invention relates to an encrypted traffic detection method based on multi-dimensional feature parallel fusion, and belongs to the technical field of network security. According to the method, when a multi-dimensional feature parallel fusion framework is constructed, the limitation of traditional statistical features on dynamic evolution characterization of encryption behaviors and the dependency of graph neural network topology modeling on computing resources are fully considered; through collaborative optimization of a Markov chain dynamic quantization protocol interaction state transition rule and a lightweight graph attention hierarchical compression mechanism, a detection model gives consideration to deep feature perception capability and efficient reasoning capability at the same time; based on the classification decision realized by the fusion mechanism, the recognition robustness and real-time defense efficiency of the encrypted malicious traffic are remarkably improved, and the active security protection level of the network is effectively enhanced.

The invention is suitable for the technical field of data asset management, and provides a data asset management system based on a block chain and big data analysis, and the system comprises a first terminal which carries out the storage of the ownership information of data assets through a block chain network, and generates a storage data package; generating an evaluation result based on a preset technical index analysis model; writing the hash value of the evaluation result into transaction data of the main chain of the block chain, and generating an evidence storage voucher matched with the block chain transaction; an interaction data sequence is packaged for identity signature, encryption and compression to generate a target code stream, and the target code stream is sent to the second terminal; the second terminal decrypts the encrypted data in the target code stream by using a private key, decompresses the data by using a compression algorithm matched with the first terminal, and restores the data into an interactive data sequence; verifying the access authority and the transaction condition of the evidence storage data packet; checking the anchoring state of the evidence storage voucher on the main chain of the block chain; and the data transaction is completed, the data asset state report is generated, and the data element marketization configuration efficiency is improved.

The invention provides a data privacy protection method for a data governance system, and belongs to the technical field of data governance, and the method comprises the steps: carrying out the cross verification of multi-source feature data and the unique identification information of an object collected on site, generating an original data set, carrying out the sensitive information recognition and grading, and generating the preprocessing data with a sensitive grade label; core identification information in the preprocessed data is disassembled to generate standardized desensitized data conforming to privacy protection, a bidirectional encryption mapping relation is established between object unique identification information collected on site and the standardized desensitized data, an encryption index is formed, the encryption index and preset multi-dimensional compliance data are fused, and a data fusion result is obtained; generating standardized fusion data; and based on the access token, generating a differential authorization data set divided according to permission granularity, performing privacy disclosure risk assessment, generating a risk level, performing privacy processing on the risk level, and outputting the risk level to a risk control system. And the data management efficiency is improved.

The invention relates to the technical field of information security, provides an intelligent warehouse login verification method and system based on dynamic living body detection, and is used for realizing accurate generation of an identity label vector, enhanced authentication of a dynamic password and automatic matching of warehouse authority while accurately performing living body detection. And the security and convenience of warehousing system login are comprehensively improved. The method comprises the following steps: collecting real-time interaction action data of a warehousing system login user, calling a preset living body detection algorithm to carry out dynamic biological characteristic analysis on the real-time interaction action data, and generating a living body verification confidence coefficient and a user identity identification vector; performing dynamic password enhanced authentication according to the living body verification confidence coefficient and a preset security authentication threshold value, and generating a dynamic access token containing multiple layers of encryption identifiers; and based on the user identity identification vector and the dynamic access token, executing storage permission automatic matching processing, and outputting a login verification result associated with the user permission level to the storage system according to the permission matching label.

The invention discloses an intelligent water level monitoring system and a data transmission method thereof, and belongs to the technical field of Internet of Things sensing. The system comprises a distributed water level sensing node, an edge computing gateway and a cloud management platform, wherein the sensing node is integrated with a piezoresistive water level transmitter and an adaptive Kalman filtering module; the data transmission method comprises a dynamic threshold triggering mechanism and a compression algorithm based on improved Huffman coding, and low-power-consumption and high-reliability transmission is realized by optimizing transmission frequency and a data packet structure. The edge computing gateway is internally provided with an LSTM water level prediction model, historical data are analyzed through an LSTM neural network, and an early warning signal is generated in real time. And the cloud management platform stores the key data by adopting a block chain technology. Through multi-sensor data fusion and layered encryption transmission, the water level monitoring error rate is reduced to + / -0.5 cm, the data transmission energy consumption is reduced by 40%, and the monitoring efficiency and the data safety are remarkably improved in flood early warning and reservoir management scenes.

The invention relates to the technical field of intelligent regulation and control of a heat supply system, in particular to a heat supply system hydraulic unbalance real-time correction method and system based on federated learning, and the method comprises the steps: constructing a temperature prediction model based on an LSTM neural network, deploying federated nodes at each user side, collecting multi-dimensional heat supply data in real time, and carrying out the preprocessing; local model parameters are encrypted and uploaded to a central server through a federated learning framework, global model parameters are generated based on verification set error dynamic weighted aggregation, and nodes are reversely updated; the updated model is used for predicting the heat load in the next one hour, the valve opening degree is dynamically adjusted in combination with a hydraulic equilibrium algorithm, and whole-network flow and heat demand matching is achieved. According to the method, data privacy is guaranteed through federated learning and a block chain technology, edge calculation and LSTM time sequence prediction are combined, the problems that a traditional method is high in data transmission delay, high in privacy risk and poor in model generalization are solved, and the real-time response capability and the energy utilization efficiency of a heat supply system are remarkably improved.

Systems and methods for securing agent communications in a multi-agent system including deploying an agent to communicate with external servers, instantiating a sidecar security service in communication with the agent and including at least one of a guardrails service, a security layer, an encryption module, and an integrity checker configured to validate resources tools using hash-based verification mechanisms. Communications including messages between the primary and the external servers are intercepted by the sidecar security service, which then performs at least one of filtering the one or more messages by the guardrails service, authenticating one or more server connections by the security layer, encrypting one or more outbound requests by the encryption module, or verifying an integrity of resources and tool definitions by the integrity checker.

The invention relates to the technical field of enterprise data encryption, and discloses an enterprise data encryption method and system based on artificial intelligence, and the method comprises the steps: collecting internal and external heterogeneous data streams of an enterprise, carrying out the standardization processing, and recognizing potential risk features through combining time sequence alignment and vulnerability analysis; a risk probability analysis tool is utilized to carry out quantitative evaluation from two dimensions of data sensitivity and an influence range, an encryption parameter adjustment scheme is dynamically generated, calculation and storage resources are dynamically allocated according to a scene risk level, an encryption strategy is updated in real time, and hierarchical protection is carried out on sensitive information. According to the method, corresponding encryption strength can be adopted for data of different risk levels, resource utilization is optimized while safety is guaranteed, the data leakage risk is effectively dealt with, and the enterprise information safety protection capability is improved.

A method for updating a device, including: receiving, by the device, a public one-time signature key; receiving, by the device, a secret encryption key; receiving an encrypted update package and signature from an update provider; verifying the signature using the public one-time signature key; decrypting the encrypted update package using the secret encryption key; and updating the device using the decrypted update package.

The invention relates to the technical field of monitoring systems, in particular to an electromechanical equipment control method and system for building intelligent system integration. Comprising the following steps: collecting operation parameters of electromechanical equipment and building environment parameters in real time; the operation parameters and the building environment parameters are transmitted to a central control unit through a communication network; the operation parameters of the central control unit and the building environment parameters are input into a preset evaluation model, and the operation state and abnormality diagnosis information of the equipment are output; generating a corresponding control strategy through an intelligent algorithm; the control command is converted into a control command through the central control unit and is sent to the execution mechanism through the communication network, and the execution mechanism regulates and controls the electromechanical equipment and sends a feedback signal to the central control unit. The multi-source sensor is used for collecting operation parameters and environment parameters in real time, and the data precision is guaranteed in combination with a self-calibration mechanism; meanwhile, data interference and leakage risks are reduced through encryption processing, and a high-quality data basis is provided for subsequent analysis.

The invention relates to the technical field of big data, and discloses a resource pool planning method based on a computing power network, comprising the following steps: S1, global resource modeling; s2, intention-driven resource slicing; s3, intelligent scheduling and load balancing; s4, predictive fault-tolerant self-healing is carried out; s5, energy efficiency optimization resource recovery; according to the method, a safe and efficient distributed computing power network resource awareness framework is constructed by fusing a dynamic key agreement protocol and a federated learning mechanism; according to the new method, the resource discovery accuracy, the state updating timeliness and the abnormal node recognition capability are remarkably improved, and meanwhile, the privacy leakage risk in cross-domain collaboration is effectively avoided through the national secret algorithm encryption, block chain auditing and zero-knowledge certification technologies; according to the method, greenization and high efficiency of resource allocation are realized through a carbon perception dynamic scheduling strategy and a multi-objective optimization model; tasks are preferentially scheduled to green energy nodes, energy consumption of idle nodes is reduced in combination with a dynamic frequency modulation technology, and system energy consumption and carbon emission are reduced.

The invention discloses a cross-domain privacy protection method and system for advertisement recommendation, equipment and a medium, and the method specifically comprises the steps: carrying out the encryption matching of user behavior data and anonymized equipment data, and generating an initial cross-domain joint feature vector; fusing the initial cross-domain joint feature vector and the disturbance feature vector to form a target cross-domain joint feature vector; splitting a pre-trained advertisement recommendation model into a feature coding sub-module and a reasoning sub-module, deploying the feature coding sub-module to a user adjacent edge node, and retaining the reasoning sub-module in a user local device; and based on the target cross-domain joint feature vector, performing calculation of the feature coding sub-module and calculation of the reasoning sub-module, and uploading the encrypted hidden layer feature vector to a federated learning aggregation server for global model updating. According to the method, cross-domain data utilization and user privacy protection in an advertisement recommendation process are realized, and effective feature vectors are generated for personalized advertisement recommendation while data are guaranteed not to be out of a domain.