92 results about "Distributed hash table" patented technology

The invention provides a distributed power data asset management privacy protection encryption architecture design method, which comprises the steps of generating a watermark with robustness and imperceptibility by adopting a content-based digital watermarking algorithm according to statistical characteristics of power data assets, and storing a watermark embedding process and an extraction result through a blockchain; a graph-based data model is adopted, the electric power data assets carrying the watermarks serve as nodes, the data flow relation serves as edges, and an electric power data asset consanguinity graph is constructed; for distributed storage of the blood relationship map, a P2P network topology is constructed by adopting a block chain and a distributed hash table, and blood relationship map data is stored in each node of an alliance chain in a distributed manner; and verifying the digital watermark information embedded in all circulation path nodes through which the power data assets pass in the blood relationship map, calculating the similarity between the extracted watermark and the original watermark, calculating the distortion rate, and judging whether the power data assets are tampered or not.

The invention relates to the technical field of data processing, in particular to a cloud backup platform data deduplication method based on distributed storage. Comprising the following steps of: performing self-adaptive blocking on data by utilizing a dynamic blocking algorithm, generating a unique identification code and extracting multi-dimensional feature information; establishing a global index through a distributed hash table, mapping a data position and maintaining index consistency; performing redundancy analysis and similarity matching based on a deep learning algorithm, and executing a duplicate removal strategy; according to the access frequency and the load condition, distributed storage of data blocks is realized by adopting a hierarchical graph division algorithm; and a partitioning strategy, index frequency and storage layout are dynamically optimized by using a reinforcement learning algorithm, and global optimization of performance and resources is realized. According to the invention, high efficiency, accuracy and dynamic optimization of data deduplication are realized, and the data storage and management efficiency of the cloud backup platform is improved.

The invention provides a data privacy protection method, which comprises the following steps of: acquiring an original data set, extracting a high-sensitivity field, calculating the correlation between the high-sensitivity field and other fields, and determining a high-correlation field combination; performing intelligent segmentation and scattered storage on the high-relevance field combination, and constructing a distributed hash table index; realizing encryption aggregation and asynchronous updating of global model parameters through a federated learning framework; constructing an adversarial sample for the high-relevance field combination, and training a privacy protection defense model; differential privacy perturbation processing is carried out on the high-sensitivity field; calculating an association risk index of the high association field combination in real time, and generating an association risk analysis report; dynamically adjusting a data segmentation strategy according to the associated risk analysis report, and optimizing local model training sample selection; and if the association risk index exceeds a preset security threshold, triggering adaptive updating of a differential privacy deassociation processing flow.

The invention discloses a big data resource service method and system based on multi-modal data fusion, belongs to the technical field of big data processing, and solves the problems that a scheduling scheme is formulated only by calculating an energy consumption value and a resource utilization rate of a server in an existing method, the adaptability to dynamic changes is poor, and the overall performance and the resource utilization rate of the system are reduced. The method comprises the steps that a multi-modal data sequence is preprocessed, a shared database is created, multi-modal data are encrypted and distributed to a distributed hash table of distributed nodes, a resource retrieval instruction is recognized based on a resource scheduling model, and the resource scheduling model dynamically deploys a data transmission task based on target data attributes and real-time transmission path information; according to the method, the resource scheduling model considering the multi-modal data distribution and transmission characteristics in the distributed environment is constructed, collaborative learning and optimization among distributed nodes are realized, the transmission path is dynamically optimized, the delay and energy consumption of data transmission are reduced, and the intelligent level of scheduling is improved.

The invention provides a 5G message transmission method and system based on privacy protection, and relates to the technical field of communication. The method comprises the following steps: encrypting the content of a to-be-sent 5G message to generate an encrypted message; dividing the encrypted message into a plurality of encrypted message fragments, generating corresponding confusion information for each encrypted message fragment, and encrypting the sensitive metadata to form a first data packet; generating a second data packet containing anonymous verification information based on the first data packet; determining a plurality of transmission paths by using a multi-path selection algorithm in combination with a routing selection strategy, and performing task allocation for each transmission path by using a distributed hash table to obtain an allocation result; and performing scattered transmission on all the second data packets according to the distribution result, so that the message receiving equipment performs recombination and decryption processing on all the second data packets to recover the 5G message content. According to the technical scheme provided by the invention, privacy protection is enhanced, and the security and reliability of 5G message transmission are ensured.

The invention discloses an efficient file uploading and downloading method and system, and belongs to the technical field of information technology and cloud computing, the method is implemented by the following steps: preprocessing a file to be transmitted, the preprocessing comprising compressing the file by using a data compression algorithm and extracting file metadata; segmenting the preprocessed file into a plurality of small blocks, and generating verification information for each small block; determining an optimal storage position of each file block by utilizing a distributed hash table technology; the edge computing node assists in executing part of operation tasks to accelerate the transmission process; whether some files or parts of the files are cached on edge nodes or not is intelligently decided according to the user behavior analysis result; when a user needs to download a file, the client firstly checks whether an available cache exists locally, and if not, the client requests the file from the cloud and obtains each file block as required. According to the method, the file uploading and downloading speed can be effectively improved, and the probability of errors in the transmission process is reduced.

The invention discloses a lightweight block chain node consensus mechanism optimization method, and relates to the technical field of block chains. According to the method, the computing power of the lightweight nodes is accurately evaluated through a hierarchical verification aggregation algorithm, efficient participation of the lightweight nodes in a resource-constrained environment is realized, a transaction set is divided into a plurality of subsets by adopting a transaction verification fragmentation strategy, and verification results are aggregated by utilizing a Merkel tree aggregation verification technology; in addition, a dynamic storage management strategy is established, the depth of locally stored historical data is dynamically adjusted according to the node storage capacity, and network storage and retrieval are performed through a distributed hash table; the bottleneck problem of storage and network transmission is effectively solved, and the network bandwidth utilization efficiency and the storage management flexibility are improved.

The invention discloses a multi-level privacy protection data sharing method and system based on a block chain. The method comprises the following steps: S1, collecting and uploading original data; generating an encryption key by adopting a dynamic DNA coding sequence and combining an AES key expansion method, encrypting the collected data by utilizing the generated encryption key to obtain an encrypted file, and storing the encrypted file in a local storage library; s2, uploading the encrypted file in the step S1 to a distributed hash table of an IPFS distributed storage system through an SHA-256 hash function, and verifying and confirming a block by adopting a dynamic hybrid consensus mechanism; s3, accessing the block chain by the user through the smart contract, and executing space-time double-attenuation permission control; and S4, after the permission verification is passed, a decryption key is provided for the user, and the user performs data decryption by using an AES decryption algorithm and DNA reverse coding. According to the method, more accurate authority management can be provided, the security and compliance of data access are improved, and the method is suitable for management of large-scale data.

A full-link data security protection method and a system are provided. The method includes: at a data creation and collection stage: building a data security identification; at a data transmission and storage stage: dividing the ciphertext file into blocks to generate ciphertext components; calculating a virtual index and a data label; transmitting the ciphertext components to a distributed hash table (DHT) network; uploading a tuple including the virtual index, the data block, and the data label to a cloud server; at a data processing and exchange stage: applying re-encryption based on a re-encryption key generation algorithm; performing decryption to obtain the signed identifier and a secret value; acquiring a tuple having a ciphertext component associated with the virtual index. Attribute-based proxy re-encryption is used to achieve fine-grained access control for the cloud storage. In the data destruction stage, the DHT network automatic updating utility is leveraged to realize data self-destructing.

The invention relates to the field of virtual reality simulation, and discloses a virtual laboratory simulation system and method based on the VR technology, and the method comprises the steps: obtaining user interaction data through a sensor, carrying out the preprocessing, transmitting the user interaction data in real time through a network communication protocol, carrying out the data fusion and synchronous processing, and updating scene data, transmitting the updated scene data to the user; a scene synchronization value is calculated through network delay and equipment performance difference, scene data is fused with space-time three dimensions to perform synchronization verification, and a scene state synchronization algorithm based on a distributed hash table is adopted to monitor the change of a scene state and perform dynamic adjustment; detecting and compensating the operation delay of the user, establishing an operation delay model, predicting the operation action of the user, and executing the operation action in advance in the virtual scene; according to interaction data of an object in a virtual scene, an interactive friction tactile feedback signal is generated in real time, and tactile feedback is controlled by combining a pressure sensor and vibration motor hardware equipment.

A secure method for exchanging entities via a blockchain is presented. The method comprises receiving, from a user over a communications network, an invitation to perform an exchange of entities; generating a redeem script comprising metadata; hashing the redeem script to generate a redeem script hash; sending the first script and the first script hash on a distributed hash table (DHT); and generating an invitation transaction comprising an output associated with an encrypted digital asset, and a hash of a script comprising an indication of entities to be exchanged, conditions for the exchange, and a public cryptographic key associated with the user.

The invention belongs to the technical field of Internet security, and discloses a public Internet of Things privacy protection identity authentication method and system based on a block chain, which do not depend on a centralized server, adopts a storage mechanism based on a distributed hash table to realize data storage in a chain-on-chain and chain-off mode, realizes decentralized storage and improves the security of data. Identity sources of the sensor nodes are authenticated through an intelligent contract technology under the condition that real identities are not needed; the method has unforgeability under a random oracle model, and meets the security requirements of integrity, authentication, anonymity and traceability at the same time.

The invention provides an electronic file distributed storage method based on content sensitivity classification encryption and fragmentation redundancy, and aims to improve the safety and reliability of an electronic file storage system. The method comprises the following steps: firstly, carrying out content classification on electronic archives, and carrying out hierarchical encryption according to sensitivity to ensure that different types of archives have adaptive security policies; then, the encrypted archive data is subjected to fragmentation processing and redundancy distribution, so that the fault-tolerant capability and the access efficiency of the data are improved. Fragmented data is stored to a plurality of nodes through a distributed network, and rapid positioning and retrieval are carried out by using a distributed hash table. In a data access process, a user authority management and key distribution mechanism is combined to ensure that the user can only access the archive information within the authority range of the user. The method effectively solves the problems of data security, privacy protection and system robustness in electronic archive distributed storage, and is suitable for various archive management scenes.

The invention relates to the technical field of commercial financial information processing, and provides a commodity market dynamic prediction method and system, a medium and electronic equipment. Acquiring real-time market information data of the target commodity and submitting the real-time market information data to a market information staring system; verifying the real-time market data, generating a data set hash value based on the target data passing the verification, aggregating the target data in a distributed hash table, and storing the aggregated data in a block chain based on the data set hash value; formulating a transaction strategy based on the target data, encoding the transaction strategy into a smart contract, and deploying the smart contract on the block chain; and when the market dynamic condition of the target data is predicted to meet the triggering condition of the smart contract, automatically executing the transaction. On the basis of ensuring the data accuracy and security, the transaction is automatically executed when the market information dynamically accords with the intelligent contract, so that the intelligence, automation and high efficiency of transaction decision making are realized, and the response speed and execution precision of commodity transaction are greatly improved.

The invention discloses a large model reasoning method and device based on cross-domain edge device collaboration, and the method comprises the steps: dynamically sensing the available resource condition of a graphics processor in a plurality of working nodes based on a distributed hash table, and distributing a large model block to the working nodes according to the available resource condition; the available resource condition represents an unallocated working node set; receiving a user reasoning request, wherein the reasoning request at least comprises one or more reasoning tasks; based on the large model blocks allocated by the working nodes, allocating the reasoning tasks to one or more management nodes; an area where each management node is located comprises a working node set; the management node distributes the reasoning task to the working node set of the region for reasoning; the working node set comprises a plurality of working nodes. By means of the method and device, the efficiency of the distributed reasoning task can be improved, and flexible allocation of resources and high reliability of the system can be achieved.

The invention discloses a cloud edge efficient synchronization mechanism and distributed management scheduling system based on crop water shortage data, and relates to the technical field of intelligent agriculture. The system comprises an edge end, an edge computing node module, a cloud edge communication module and a cloud storage and management module, wherein the edge end is used for collecting multi-source original data related to crop water shortage; the edge computing node module is used for preprocessing the multi-source original data and extracting a feature vector comprehensively reflecting a crop water shortage state; the cloud side communication module is used for constructing a two-way communication link and adjusting the data transmission rate according to an adaptive window adjustment strategy; and the cloud storage and management module is used for carrying out encrypted storage on the data by adopting a distributed hash table technology and carrying out dynamic scheduling and distribution on the stored data by utilizing a distributed management scheduling algorithm. According to the invention, efficient collection, accurate transmission, intelligent scheduling and safe storage of crop water shortage data can be realized, and agricultural data management precision and decision-making efficiency are improved.

The invention discloses a power operation management and control method and system based on big data pre-compression gridding processing, and the method comprises the steps: S1, carrying out the pre-compression through a data partitioning mechanism and dynamic dictionary compression; s2, performing gridding processing through three-dimensional grid division and anomaly detection; s3, on the basis of a genetic algorithm and a particle swarm optimization algorithm, performing optimal state mining on a gridding processing result; s4, on the basis of the electricity price prediction result and the optimal state mining result, determining the enabling rate of each device and the corresponding output power parameter; and S5, carrying out visual output. The system is used for supporting the method to operate. Through the distributed hash table and double-layered dictionary coding, mass data are quickly compressed, and the calculation load is reduced; carrying out multi-dimensional grid division and hybrid algorithm calculation, and carrying out accurate positioning and obtaining optimal operation parameters; and electricity price prediction, decision scheme generation and visual display are carried out, so that the management and control process is more visual.

This invention discloses a distributed data query method and system for ubiquitous storage. The method comprises the following steps: Step 1, constructing a hierarchical index network model, which includes a metadata management network and a data block index network: a decentralized metadata management network is constructed using a fully connected networking approach; a data block index network is constructed based on a distributed hash table; Step 2, defining a hierarchical data index interaction paradigm to achieve collaborative management and fast querying of metadata and data blocks. This invention, through the hierarchical index network model, decouples metadata from location information, reducing the management and maintenance costs of metadata.

The invention discloses a linear communication complexity consensus method based on a DAG structure, and belongs to the field of computer science and technology. According to the invention, an efficient BFT consensus method is established by optimizing a communication process and introducing a broadcast mode of linear communication complexity. According to the invention, a broadcast mode (VBC) with linear communication complexity is introduced to replace the traditional reliable broadcast (RBC), so that the communication complexity is greatly reduced, and the efficiency of the system is improved; in addition, the communication complexity is effectively reduced, the system can process more transactions, the throughput of the system is remarkably improved, and the requirement of large-scale application is met; furthermore, a broadcast mode (VBC) with linear communication complexity enables the communication overhead not to be obviously increased when the number of nodes of the system is increased, so that the expandability of the system is improved, and the method is suitable for a larger-scale distributed network; and finally, by combining a distributed hash table and a threshold signature technology, the system can still maintain high-level security and fault tolerance and prevent attack of malicious nodes while the communication complexity is reduced, the throughput of the system can be remarkably improved, the expandability of the BFT consensus system in large-scale application can be realized, and the method is suitable for popularization and application. Therefore, a major breakthrough is brought to the development of a distributed system and a block chain technology.

The application relates to the technical field of data security, in particular to a cloud file destruction and data tracing method and system, which comprises the following steps: a distributed hash table algorithm is used to analyze a physical storage unit set of a cloud file to be destroyed; a chaotic sequence multiple overwriting operation is used to forcibly clean the physical layer; a storage unit state flip matrix is collected in real time, and a Shannon entropy value is calculated; a cryptography destruction certificate is generated after the Shannon entropy value breaks through a safe destruction baseline; and finally, the certificate is encapsulated into a terminal block of a full life cycle tracing chain. In the application, the chaotic overwriting based on the entropy value detection is executed by analyzing the physical storage unit set, and the residual magnetic characteristics of the data in the physical layer are forcibly destroyed, so that the hidden danger of false deletion in the cloud environment is solved, the unalterable destruction evidence is established in combination with a chain locking mechanism, and the safe closed loop of the data full life cycle is realized.

A method for restoring data on a client node in a network includes receiving, by a first node and from the client node, a restoration request for a first version of a requested data asset; querying, by the first node, a distributed hash table (DHT) to identify a second node in a plurality of nodes storing a second version of the requested data asset; verifying, using a distributed ledger table (DLT), that the second version of the requested data asset stored on the second node matches the first version; and initiating, based on the verifying, a data transfer of the second version of the requested data asset from the second node to the client node.

Techniques and computer-implemented methods are presented to be implemented on a distributed mempool network (DMP) implementing a distributed hash table (DHT). The method includes: receiving, at a mempool node of a DMP, a request to update routing information of the mempool node; initializing a set of random walks within a key space of the DHT, the set of random walks used for generating a set of key-value records; selecting a particular iteration of a long-distance table of a set of long-distance tables; selecting, from the particular iteration of the long-distance table, a pointer within a range between identification information and a key; and transmitting a query to another mempool node associated with the pointer, wherein the other mempool node maintains a set of weight associated connections to a set of mempool nodes, wherein the weight is proportional to the level of trust in the connection.

The invention discloses a directory-type distributed data structure implementation method and system, belongs to the technical field of data storage and concurrent processing, and aims to solve the technical problems of poor expandability and low performance of a traditional data structure under a non-cache consistency / partial cache consistency multi-core architecture. Comprising the following steps: dividing a multi-core architecture into a plurality of consistent islands, connecting the islands through a high-speed packet-loss-free network, and performing cross-island communication between cores through two communication primitives; a distributed hash table DHT is constructed, each server node maintains a plurality of hash buckets, the hash buckets adopt a linked list to solve conflicts, and a target server node and the hash buckets are positioned through a hash function; a server node is selected as a synchronizer, the synchronizer is used for distributing or recycling operation key values for a client side, the client side achieves data structure operation of stacks, queues and double-end queues through combination of two short messages and one DHT primitive, and linearization points of all the operations only depend on the moment when the synchronizer returns the key values.

A data center storage system integrated into a core network. The system comprises a plurality of data centers that each provides a memory storage; a plurality of optical fiber communication links, wherein each optical communication link communicatively couples two of the data centers to each other, wherein the memory storage of the data centers stores a plurality of files, wherein each file is identified by a hash calculated over the content of the file, wherein a distributed hash table is stored in the memory storage of each data center that associates hashes of files to a memory storage location where the files are stored, and wherein at least some of the files are distributed across each of the plurality of data centers, whereby a vulnerability to hacking the files is decreased, and wherein each data center is connected to the core network.

The application particularly relates to a relay forwarding node selection method and system for a terminal computing power network. The relay forwarding node selection method for the terminal computing power network comprises the following steps: searching for a distributed hash table (DHT) retrieval relay forwarding node list according to network resource demand information of a deployed service, and performing preliminary screening; performing secondary screening based on available bandwidth and the number of connections, and performing DHT retrieval again to obtain associated address information multiaddr; performing connection testing, filtering relay forwarding nodes that cannot meet the demand, and establishing a relay connection; monitoring performance data of the relay connection, and re-searching for applicable relay forwarding nodes if the network resource demand is not met. The relay forwarding node selection method and system for the terminal computing power network can update connection resource information of relay forwarding nodes providing relay services in a timely manner, meet network resource demand, realize communication between a service providing node and a service consuming node, and guarantee connection quality of the service.

The application belongs to the technical field of cloud computing and information security, and discloses an education resource sharing method and system based on cloud computing. The method carries out structural analysis on online course resources uploaded to a cloud platform, defines a user role attribute model based on an education scene, constructs an access control policy tree based on an attribute-based encryption mechanism, adopts a distributed hash table to store fragments of the resource ciphertext, and generates a resource positioning index. When a course resource access request is received, the education attribute set of the requesting user is verified, and a learning path perception mechanism is combined to determine whether the user meets the decryption condition and chapter unlocking condition of the access control policy tree. The course access record, learning duration, test score and credit acquisition record of the learner are recorded to an education alliance chain to generate a verifiable learning record certificate, thereby realizing access tracing and auditing. The technical problems of coarse education resource access control granularity, weak anti-stealing broadcast capability and low learning record credibility are solved.

This invention discloses a management method for trusted blockchain data, belonging to the field of trusted data technology, comprising the following steps: S1, constructing a four-layer architecture of "privacy enhancement layer - dynamic consensus layer - cross-chain collaboration layer - value mining layer," with each layer achieving collaborative linkage through intelligent interfaces; S2, the privacy enhancement layer adopts a scheme integrating zero-knowledge proof, homomorphic encryption, differential privacy dynamic noise injection, and blockchain key sharding management; S3, deploying an enhanced adaptive consensus switching mechanism in the dynamic consensus layer; S4, constructing a cross-chain mapping network based on a distributed hash table in the cross-chain collaboration layer; S5, introducing an enhanced federated learning framework in the value mining layer. This invention, employing the above-mentioned management method for trusted blockchain data, allows the strength of privacy protection to adapt to scenario requirements, significantly improves the identification and response speed of malicious nodes, enhances cross-chain collaboration capabilities, and makes data value mining more accurate.

The invention provides a method and a device for realizing a network function, which are used for realizing the network function under the condition that a distributed network architecture meets credible requirements. The method comprises: a sixth NF network element receiving first information from a first network function NF network element and second information from a second NF network element; acquiring a first model and first data according to the second information; and determining the response of the business demand according to the first model and the first data. The second information indicates a storage condition of data required for realizing a service demand in a third NF network element, the second NF network element is used for recording the storage condition of the data by adopting a distributed account book technology, the third NF network element is used for storing the data by adopting a distributed hash table technology, and the data comprises model data corresponding to a model type and first data corresponding to a data type; the model data is used to determine a first model.