483 results about "Merkle tree" patented technology

The invention relates to the technical field of block chains, and discloses a supply chain tracing method and system based on a block chain, and the method comprises the steps: carrying out the collection and feature learning of the product identification information and transaction records of a supply chain node, and obtaining a supply chain transaction feature vector; based on the supply chain transaction feature vector, executing intelligent contract verification strategy confirmation and weighted voting verification on a transaction group to obtain a consensus confirmation block; extracting transaction data from the consensus confirmation block, constructing a double-Hash Merkle tree structure and generating supply chain traceability features; and executing a commodity tracing contract, a quality verification contract and a responsibility judgment contract according to the supply chain tracing characteristics, and generating an execution log and a visual tracing report, thereby reducing the number of verification nodes and network communication overhead while ensuring the block verification reliability, improving the consensus efficiency, and improving the objectivity and efficiency of the tracing process.

The invention relates to the technical field of data mining, in particular to a data security management system and method based on cloud computing. The method comprises the following steps: acquiring real-time vehicle driving data, and performing homomorphic modular exponentiation dangerous case sensing fragmentation encryption to obtain dangerous case sensing encrypted fragmentation data; acquiring an Internet of Vehicles data stream, and implementing zero-trust adaptive data stream encryption to obtain a zero-trust authentication credential; implementing federal learning privacy feature mapping on the dangerous case sensing encrypted fragmented data to obtain an anonymized encrypted feature mapping model; performing Merkle tree aggregation on the anonymized encrypted feature mapping model to obtain a block chain global dangerous case fingerprint; extracting a threat behavior quantization vector according to the block chain global dangerous case fingerprint and the anonymization encryption feature mapping model; and carrying out transmission strategy optimization according to the threat behavior quantization vector and the zero-trust authentication credential to obtain a global dynamic transmission strategy matrix. According to the invention, the safety of vehicle data uploading and the overall uploading efficiency can be improved.

A system for adaptively caching network communication protocols enhances efficiency across heterogeneous device environments through a multi-level cache architecture with device-capability-based tiers. The system collects endpoint telemetry data including device capabilities and operational constraints to classify endpoints and generate context-aware protocol variants optimized for specific device types. Protocol optimization opportunities are determined through structural analysis of message patterns and state transitions. The system performs protocol deduplication by identifying functionally equivalent variants and maintaining canonical representations to reduce cache redundancy. Cache synchronization across distributed nodes uses enhanced Merkle tree structures with protocol normalization processing. The system predicts communication needs based on historical patterns, network context, and endpoint constraints, enabling proactive cache management tailored to device capabilities. Integration with event-driven data communication systems enables seamless protocol selection and translation while maintaining compatibility between diverse endpoint types, from high-performance servers to resource-constrained IoT devices.

The invention relates to the technical field of accounting informatization, and discloses an accounting document cross-platform synchronization system based on a block chain and a conflict processing method, and the system automatically judges a multi-mechanism concurrent operation conflict based on a preset medical authority level and a millisecond timestamp. And when a plurality of branch hospitals modify the same patient voucher at the same time, preferentially adopting a high-authority mechanism to operate, if the authority is at the same level, selecting the operation with the latest timestamp, and if logic conflicts exist, pushing to a general hospital for manual auditing. And an operation log is recorded in real time by adopting Apache Kafka, and a non-tampering historical version is generated through a block chain technology. All modification records are stored in a Merkle tree structure, a complete operation track at any time point can be inquired through a patient ID, the complete operation track comprises modification content, operator identity and block chain transaction hash, a national medical insurance platform is connected in real time, and cost compliance is automatically verified; the system can solve the problems of data conflicts, version chaos and auditing tracing among heterogeneous ERP (Enterprise Resource Planning) systems.

The invention provides an electronic data evidence storage verification method and system based on hierarchical hash and an intelligent contract, and relates to the technical field of block chains and data security, and the method comprises the steps: obtaining to-be-stored electronic data; to-be-stored electronic data is divided into data blocks according to a preset rule, a unique identifier and a timestamp are added to each data block, and a standardized data unit is generated; performing hierarchical hash calculation on the standardized data unit, generating a leaf node hash value by each data block, aggregating the leaf node hash values layer by layer according to a Merkle tree structure, and generating root hash; calling a block chain smart contract, submitting the tree structure hash, the timestamp and the public key encrypted signature to a block chain network, after verification of a consensus node, writing the evidence information into the block chain, analyzing a hash path submitted by a user by the smart contract to perform data verification, if the hash path is consistent with the data verification, returning verification success, otherwise, triggering an exception handling contract; through the dynamic partitioning algorithm and the layered hash structure, the calculation overhead of large file processing is reduced.

The invention relates to the technical field of information retrieval, in particular to a software copyright management system based on a smart contract, which comprises a copyright level right confirmation module, an NFT fragmentation evidence storage module, a dynamic right confirmation verification module, a fragment recombination tracking module and a transaction authorization management module. According to the method, copyright data hash mapping is constructed based on a block chain hierarchical right confirmation mode, a software copyright evolution path is defined, evolution integrity is ensured by calculating hierarchical hash values and adopting Merkle tree structure storage and association of copyright information of different hierarchies, right confirmation data is split and stored in a fragmentation evidence storage mode, safety is improved, and storage and retrieval burdens are reduced; a dynamic right confirmation mechanism is combined with hash comparison and public key signature, real-time verification of newly added copyright information is achieved, it is ensured that the copyright inheritance relation is accurate and checkable, hash calculation based on code fragments, code change tracking and derivative copyright confirmation verification are achieved, and an intelligent contract is used for transaction authorization management, transaction matching and rule verification execution and copyright circulation compliance is ensured.

The invention provides a data interaction security privacy protection method and system based on a block chain. The method comprises the following steps: deploying block chain consensus nodes in a cloud to construct a main chain, deploying computing nodes in double-layer trusted execution environment hardware, and constructing sub-chains according to service types. A main chain-subchain architecture is established through a cross-chain communication protocol, and a cross-chain smart contract is deployed. And receiving a user data interaction request, verifying the identity, and granting access or uploading authority. And generating a data fingerprint and an operation log, and organizing the data fingerprint and the operation log into a Merkle tree structure. A hierarchical storage architecture based on a DAG is adopted, and data and log Merkle trees are stored in a main chain-subchain architecture. In the whole process, data security, privacy protection and traceability are ensured, and an efficient and reliable block chain data management system is realized.

The invention provides a commodity data management method based on a block chain, and the method comprises the steps: obtaining commodity attribute data, carrying out the standardization processing of the commodity attribute data according to a pre-established commodity attribute standardization mapping table, and obtaining the standardized commodity attribute data; writing the standardized commodity attribute data into a target data fragment of a distributed account book storage architecture according to a preset data routing rule, and indexing by adopting a Merkle tree data structure; legality and integrity verification is carried out on the data writing operation through an intelligent contract automation mechanism, and data index information is generated; and according to the commodity attribute and the transaction identification code, determining the data integrity and non-tampering through the block hash value, obtaining the traceability rule in the smart contract, judging the data security, and obtaining an automatic traceability process.

The invention relates to the technical field of carbon footprint dynamics, in particular to a railway traffic carbon footprint dynamic tracking system and method based on a block chain and edge calculation. The data acquisition unit is used for acquiring train operation state, environment parameters and traction energy consumption data; the edge calculation unit fuses the multi-source data acquired by the data acquisition unit through adaptive Kalman filtering to obtain standardized data, converts a train operation state into carbon emission based on an instantaneous power model, and introduces a dynamic emission factor to calculate and obtain accumulated carbon emission; and the block chain network unit is used for compressing the accumulated carbon emission data and then generating a Merkle tree root hash upper chain, and storing the carbon emission data to a block chain. Incremental uplink and rapid verification of the data are realized, the on-chain data processing efficiency and the query traceability are improved, and the problems of high storage pressure and low verification efficiency of a traditional on-chain evidence storage mode in a high-frequency track data writing scene are solved.

The invention discloses a food production traceability management system based on a block chain, which belongs to the field of food management systems, and is characterized in that a unique identifier ID of an inheritor is generated based on an SHA-256 Hash algorithm, a Merkle tree root Hash value of food production data is dynamically associated, a non-tampering digital identity file is constructed, a data island of traditional decentralized management is broken through, and the traceability of food production is improved. According to the technical scheme, full-chain credible association between the non-abandoned technology and the production process is ensured, validity of an electronic signature is automatically verified by means of an intelligent contract, data tampering or identity failure risks are recognized in real time by comparing a public key decryption result with a signature hash value, JSON format alarms are pushed by means of Apache Kafka message middleware, cross-department collaborative response is achieved, and the security and reliability of the electronic signature are improved. The risk prevention and control efficiency is remarkably improved, encryption signature is performed in combination with an ECDSA key pair of a hardware security module, strong binding of an inheritor identifier, a production batch and equipment is ensured, identity fraudulent use or qualification counterfeiting is prevented, and traceability of the whole life cycle of non-abandoned skill inheritance is achieved.

The invention discloses a data ownership verification and authorization control method based on zero knowledge proof. The method comprises the following steps: constructing a traceable Merk tree structure on a block chain or a distributed account book; a data owner calculates data fingerprints and packages the data fingerprints into declaration nodes to be inserted into the traceable Merk tree; storing the ownership zero knowledge proof and the traceable Merk tree root hash into a block chain together; the verification party executes the zero-knowledge verifier contract on the chain to complete ownership verification without reading original data or identity plaintext; access control is realized after on-chain verification of the service party; triggering local heavy hash to update the traceable Merk tree root hash, and broadcasting a revocation event on a chain; and confirming legality of evolution and authorization change of all nodes. According to the method, the historical traceability and structural consistency of the data ownership and authorization relationship are ensured, and efficient traceability and anomaly detection of the node evolution chain are also realized.

The invention provides a motion data security management method and system in meta-universe smart motion, and relates to the technical field of meta-universe, and the method comprises the steps: obtaining user motion data and identity information, building an identity authentication model based on a zero-knowledge proof mechanism, generating Merkle tree zero-knowledge proof, and verifying the authenticity of the user identity. Carrying out distributed storage on the motion data by adopting a fragmentation storage technology; and providing corresponding data according to the access permission level of the third-party application. According to the invention, privacy protection and efficient storage of user data are realized, multi-level data access control is supported, and data security and utilization efficiency are improved.

The invention relates to the field of machine learning, in particular to a model weight confirmation method and device based on a block chain and a model fingerprint, and the method comprises the steps: carrying out the abstract compression of a model weight of each layer of network of a model, and obtaining a model weight abstract; performing Hash encryption and recording on the model weight abstract generated each time by adopting a Merkle tree structure to obtain a model fingerprint record; and uploading the model fingerprint record to the block chain network so as to verify the model fingerprint record. According to the invention, encryption processing is carried out on the model weight through the Hash encryption algorithm with the secret key, the model fingerprint is constructed in combination with the Merkle tree to generate a unique model fingerprint, the model fingerprint is uploaded to the block chain, the model fingerprint is combined with the block chain technology, a safe storage environment is provided for the model fingerprint, and the storage efficiency of the model fingerprint is improved. And the credibility of model ownership authentication and content tracing is enhanced.

The invention relates to a food traceability method based on a block chain, and the method comprises the steps: collecting production data, generating a unique data major key and an identifier, encrypting and uploading the data, and binding the data with a food batch; associating production link data, collecting processing data, performing secondary hash to generate a processing link data link, and binding a food unit after the processing link data link is linked; identifying a processing link identifier, collecting transportation data, carrying out chain association and timestamp progressive encryption and then carrying out uplink, generating a transportation link identifier and recording handover information; after full-link data are verified, sales data are collected, a full-link Merkel tree is formed through closed-loop association, a sales link identifier is generated after uplink encryption, and multi-node confirmation is triggered; a permission verification request is initiated through a query terminal, and after block chain type verification and local hash verification are carried out, a complete traceability link containing handover nodes, persons in charge and equipment information is displayed according to a time axis. According to the invention, full-life-cycle traceability of food is realized.

A computer-implemented method of attesting to a sequence of data exchanges between a group, wherein the group comprises a receiving party and one or more sending parties, and wherein the method is performed by the receiving party and comprises: receiving a sequence of two or more respective sets of data items, each respective set being sent by a respective sending party; and for each respective set of data items in the sequence: generating a respective attestation transaction, wherein the respective attestation transaction comprises a respective output locked to a respective Merkle root of a respective Merkle tree, wherein the respective Merkle tree is based on the respective set of data items and each previous respective set of data items in the sequence; and sending the respective attestation transaction to at least the respective sending party that sent the respective set.

The present application relates to the technical field of computers, and in particular to a verifiable ledger database storage extension method and system, capable of solving, to a certain extent, the problems of how to improve authenticated data structures to improve query efficiency, and balancing storage and calculation overheads caused by security requirements. The method comprises: introducing a sharding extension protocol, wherein the sharding extension protocol abstracts a database layer interface to provide transparent service for a lower-layer application; introducing a synchronization control protocol, wherein the synchronization control protocol improves a storage engine interface to implement two-tier storage with read-write separation, and defines a cross-shard transaction snapshot format on the basis of a Merkle tree and a derivative verifiable index structure; and designing a storage engine to optimize the locality of index data.

The invention relates to the field of edge computing data security, in particular to an integrity auditing method and system in an edge computing environment. The problem that an existing cloud auditing model is high in delay and large in bandwidth consumption in an edge scene is mainly solved. A lightweight audit challenge is generated through random sampling, data block aggregation operation is executed at an edge node, Merkel Hash tree path evidence is extracted, and integrity proof of dual verification is formed; and the aggregated evidence and the path evidence are verified by using bilinear mapping, so that efficient and credible auditing is realized. Dynamic data updating and accurate positioning of damaged blocks are supported, communication overhead is remarkably reduced, and real-time credibility of edge data is guaranteed.

The invention discloses a real-name DID and biological feature fusion rapid verification system, and the system comprises the following modules: a biological feature processing module which is used for generating a nested biological feature vector; the hash generation module is used for performing hash operation and constructing a Merkle tree; the real-name verification module is used for generating real-name identity data; the DID construction module is used for generating a DID document and adding a BioBinding extension field; the proof generation module is used for generating a verification record; the block chain writing module is used for forming an on-chain real-name DID record; the verification module is used for matching with the on-chain real-name DID record; the confidence control module is used for comparing the matching result with a preset verification threshold value, and if verification is passed, authorized access is completed; and if the verification is not passed, triggering a multi-factor re-verification mechanism to perform secondary verification, calculating a DID confidence value, and if the secondary verification is still not passed, executing identity freezing. According to the method, multi-modal biological recognition and a real-name DID generation mechanism are fused, and on-chain credible verification is realized.

A computer-implemented method of generating a digital signature for signing a message, wherein the method is performed by a coordinating party and comprises: obtaining at least the threshold number of respective signature shares; obtaining, for each of the respective signature shares, a respective commitment of the respective signature share, each respective commitment having been generated by the respective participant that generated the respective signature share; generating a Merkle tree, wherein at least the threshold number of respective leaf nodes of the Merkle tree comprise a respective hash of a respective signature commitment combined with a respective participant index, wherein the respective participant index is associated with the respective participant that generated the respective signature commitment; generating the signature based on at least the threshold number of respective signature shares; and making a Merkle root of the Merkle tree available to at least the respective participants that generated a signature share.

A system including a relational Merkle tree data store including a child node and an additional child node. The child node has a linked parent node of a first Merkle tree, the linked parent node is tagged with a hash of the child node, and the child node and the additional child node are each tagged with an inverse hash of the linked parent node prior to the relational Merkle tree data store receiving a request for a product history of a product. The inverse hash is exclusively a cryptographic hash of the linked parent node, The inverse hash is used to perform a bi-directional traversal of the relational Merkle tree data store to retrieve the product history for the request. The relational Merkle tree data store includes the product history of the product.

The invention relates to a cloud data auditing method based on a block chain, and the method comprises the steps: S1, a key generation center generates system parameters and generates a user part private key based on a user identity, a user generates an authorization private key based on the part private key and sends an authorization request to a proxy server, and the proxy server generates an encryption key pair after verifying the request; s2, a user locally performs block blinding on original data blocks, a proxy server signs the data blocks and generates a Merkel Hash tree based on a bucket structure, and a cloud service provider performs integrity verification on received user files, stores data and uploads Merkel Hash tree root values to a block chain; s3, the third-party auditing mechanism generates a challenge request and sends the challenge request to the cloud service provider after receiving the auditing request of the user, the cloud service provider generates a challenge response according to parameters in a challenge set, and the third-party auditing mechanism judges whether data stored in the cloud are complete or not based on bilinear mapping; and returning the audit result to the user and generating a transaction record on the block chain.

The invention provides an information resource multi-level data recovery method and system and a medium, and the method comprises the steps: generating a snapshot header for each snapshot, which comprises a snapshot ID, a previous snapshot hash value, a current snapshot hash value and an optional digital signature; meanwhile, hash calculation is carried out on all the blocks in the snapshot, and a Merkel tree is constructed to obtain a global hash value; when a new or updated block is detected, carrying out Hash calculation on the new or updated block, adding the new or updated block into a Merkel tree, generating a new snapshot Hash value, and writing the new snapshot Hash value into a snapshot head; and taking the hash value of the previous snapshot as a predecessor reference of the new snapshot to form chained association. In a multi-copy environment, when data recovery needs to be carried out, firstly, related snapshots are screened and determined through a snapshot index and a filter; then verifying the snapshot chain to ensure that the front and back references of each snapshot are correctly matched with the Merkel tree hash value; for block-level data, if copies are inconsistent, a correct version is discriminated through weighted consensus; and finally reconstructing the damaged block.

The invention discloses a multi-level access control and authority synchronization method for secure mobile storage, and belongs to the field of mobile storage security. Aiming at the problems of data leakage, poor authority management and the like of the mobile storage device, a multi-level access control framework, a decentralized authority synchronization mechanism and a dynamic token and zero-knowledge proof system are constructed. Generating a plurality of layers of sub-keys from a master key by using a PBKDF2 algorithm through hierarchical key generation, and associating different encryption areas and authority strategies; incremental synchronization is carried out based on a Merkle tree, and data consistency is guaranteed through a consistency verification protocol; a temporary token is generated by using a Schnorr protocol, and the permission is verified in combination with zero-knowledge proof, so that the privacy security is ensured. In scene application of a power grid and the like, a master key is activated through biological recognition, permission is loaded according to a strategy, and permission change is efficiently synchronized. According to the method, the mobile storage security and the management efficiency are improved, and accurate authority control and reliable synchronization are realized.

The invention discloses a scene-based data accurate desensitization virtual power plant user privacy protection method. The method comprises the following steps of: firstly, setting different desensitization intensities according to the sensitivity of data through a hierarchical desensitization method, and selecting different desensitization technologies to perform encryption processing or access control according to the use and use scene requirements of the data, so as to realize privacy protection and accurate desensitization; secondly, accurately identifying sensitive information in the data by adopting a sensitive attribute identification module, and matching proper desensitization intensity and strategy for the sensitive information; then, data hierarchical storage and encrypted transmission are adopted, and it is ensured that data of different hierarchies are properly protected; finally, a reasonable access control strategy is set according to different scenes and data sensitivities, unauthorized access and abuse are avoided, and meanwhile the accurate desensitization efficiency is optimized. According to the method, an efficient and safe solution is provided for user privacy protection in the virtual power plant by combining hierarchical desensitization, sensitive attribute identification, Merkle tree storage, encryption transmission and attribute-based access control.

The invention discloses an artificial intelligence model traceability and tamper-proofing method and system based on block chain enhancement, and relates to the technical field of artificial intelligence model traceability and tamper-proofing. According to the technical key points, the method comprises the following steps: carrying out simulation attack by utilizing penetration testing to obtain multi-type data containing security vulnerability data; preprocessing the multi-type data; constructing an anomaly detection and attack recognition model based on a variable parameter neural network, and training the anomaly detection and attack recognition model based on the preprocessed data; performing Merkle tree encryption on the preprocessed data and model parameters obtained by training, encoding model prediction output, embedding the encoded model prediction output into a Merkle tree structure, and completing recording on a block chain through an intelligent contract; and for a to-be-evaluated artificial intelligence model, calling the global root hash value on the block chain for verification. According to the invention, the whole process of the artificial intelligence model from data acquisition to reasoning output is verifiable, traceable and tamper-proof.

The invention discloses an intelligent medical equipment management system and method, and the method comprises the steps: achieving the decentralized credible storage of an equipment use record through a block chain technology, and guaranteeing the safety and traceability of data through an SHA-256 salted Hash and Merkle tree structure; an intelligent contract is integrated to realize automatic execution of an inventory strategy, and an intelligent scheduling system is constructed in combination with an ARIMA-LSTM hybrid model and a linear programming algorithm. The system covers core modules of data acquisition, block chain storage, smart contract, prediction optimization and the like, solves the problems of data potential safety hazards, low inventory efficiency and scheduling blindness in traditional management, is suitable for intelligent management of the medical equipment in the whole life cycle, and remarkably improves the medical resource utilization efficiency and management compliance.

The invention relates to the field of block chain technology and application security, and discloses a block chain-based APP data trusted storage and sharing method, which comprises the following steps of: maintaining a verifiable state container comprising state data and an access policy dual-Merkel tree under a chain, and recording a root hash of the verifiable state container in the block chain; for different updates, generating corresponding evidences: generating single-step evidences containing Merkel evidences for single-step updates; and generating the composite proof containing the zero-knowledge proof for the complex process. And the intelligent contract can update the root hash in an atomized manner only through verification and certification. During data sharing, data and dual Merkel proof are provided for a consumer to verify data authenticity and access legality. According to the method, complex calculation is arranged under a chain, low cost and constant overhead of on-chain verification are achieved, and meanwhile high-safety data credible storage and refined authority control capacity are provided through a dual-tree dual-certificate mechanism.

The invention discloses a digital archive supervision system based on a block chain, and relates to the field of digital archive supervision. The system comprises an archive collection module, a block chain pre-processing module, a dynamic consensus module, an intelligent contract module and a supervision module. The archive collection module preprocesses heterogeneous data through a CRNN algorithm to generate a standard data set; the pre-processing module adopts the combination of SM4 and homomorphic encryption to protect data; the dynamic consensus module dynamically adjusts the right based on the node credit score, the main chain uses a PBFT method enhanced by a threshold signature to ensure the safety of core operation, and the side chain uses DPoS-RAFT to process high-frequency business; the intelligent contract module constructs a Merkle tree through block hash, and performs automatic hash verification and triggers exception handling during access; the supervision module realizes layered examination and approval of the unfreezing application by using a decision tree algorithm; according to the system, through cooperation of multiple modules, full-process block chaining of archives from collection, encryption, consensus to supervision is achieved, and the system is suitable for credible storage and supervision scenes of digital archives.

The invention relates to the technical field of data intelligent traceability, and discloses a whole-process business data intelligent traceability method and system. The method comprises the following steps: collecting first data of a preset business link and creating a semantic tag to form a semantic tag data set; the semantic tag data set is stored in a Merkle tree structure, and a service block chain is constructed; extracting second data of each business link from the business block chain, and generating a fusion data set based on the second data; and establishing a relation graph according to the fused data set, after receiving a traceability query request, starting to search a traceability path from a starting service point in the relation graph, and outputting a traceability result, thereby ensuring the reliability of the traceability result, and solving the problems of serious data island, missing association relationship and low traceability precision of the traditional traceability technology.

The invention belongs to the cross technical field of block chain technology and supply chain finance, and provides a supply chain dynamic risk control method and system based on a smart contract, and the technical scheme is as follows: obtaining node data of each participant in a supply chain; dynamically evaluating the risk of the supply chain in combination with the obtained node data of each participant and the constructed smart contract; wherein in the basic contract, the logistics data and the invoice data are verified respectively, and a verification result is sent to the business contract after verification is passed; in a business contract, according to received enterprise data, introducing a timestamp mechanism, recording creditor's right generation time in a block chain, and realizing multi-level creditor's right splitting and merging through a Merkle tree; in the risk control contract, calculating a risk assessment index based on the on-chain data, the off-chain data and the risk assessment model; and adjusting the credit granting strategy in real time according to the change of the risk assessment index to obtain an adjusted credit granting strategy. Risk control is embedded into contract execution logic, so that the risk loss of the supply chain is reduced.