335 results about "Hash chain" patented technology

The invention relates to the technical field of financial data security, and discloses an intelligent ERP financial system data security management and authentication method. The method comprises the following steps: acquiring an original transaction data stream in an ERP system, extracting key financial fields, and dividing the key financial fields into a sensitive data set and a common data set according to a preset rule; a dynamic encryption strategy framework is constructed based on sensitive data set attributes, the framework comprises multiple levels of encryption strength parameters, and the corresponding encryption strength can be automatically matched according to the authentication level of an access request. And monitoring a system data access behavior in real time, collecting feature data, inputting the feature data into the anomaly detection model, and triggering access blocking when an output anomaly access probability exceeds a threshold value. And generating a periodic integrity verification instruction according to the sensitive data updating frequency, performing integrity verification by using a hash chain technology, recording a result and marking a tampering risk level. And based on the association relationship between the tampering risk level and the abnormal access probability, generating an updated security policy and synchronizing the updated security policy to each data access node.

The invention belongs to the technical field of transportation, and particularly relates to a block chain-based transportation box full-process traceability management method and system, and the method comprises the steps of transportation box identifier generation, initial data chaining, transportation data collection, node verification recording, automatic abnormality response, and full-process traceability. According to the method, the unique block chain encryption address and node signature verification of the transport case are adopted, and the data are linked with a physical lock through Hash chain binding and encryption chips after being linked, so that the whole-process data cannot be tampered; an Internet of Things sensor is adopted to collect temperature and humidity / position data in real time, edge calculation is adopted to filter abnormal values, and intelligent contract threshold alarm and authority freezing are carried out, so that automatic collection and response of dynamic data are realized; a block chain timestamp and a chain structure are adopted to generate a space-time atlas, binding of an operation record and a responsible person signature and a fragmented block chain support cross-regional collaboration, and multi-agent collaboration tracing and accurate positioning are realized.

The invention relates to the technical field of traffic data processing, and discloses a traffic edge computing data security sharing method and system, and the method comprises the steps: collecting traffic edge computing network multi-source heterogeneous data, and carrying out the classification standardization processing to generate a structured data set; designing a dynamic data sharing security protocol based on a multi-party security computing protocol and a homomorphic encryption algorithm; verifying the authority of a requester in a multi-level manner by using an attribute-based access control model and a zero-knowledge proof mechanism, and generating a dynamic access token; storing data by adopting a fragmentation storage and redundancy encryption strategy, and recording storage information through a hash chain; and dynamically adjusting the encryption strength and the sharing strategy according to the network threat level and the data sensitivity. The method effectively guarantees safe sharing of traffic data, accurately controls access authority, improves storage and sharing efficiency, adapts to complex network environment changes, and provides powerful support for development of an intelligent traffic system.

The invention discloses an RFID anti-tracking bidirectional authentication method and system based on a lightweight hash chain, and relates to the technical field of wireless radio frequency identification security. The system comprises a label initialization module, a bidirectional authentication module, an anti-tracking mechanism module, a hash chain updating module, a secure communication module and a system feedback optimization module. The label initialization module generates initial hash chain data; the bidirectional authentication module adopts a bidirectional challenge-response mechanism to generate a dynamic authentication certificate; the anti-tracking mechanism module generates an untraceable session key through Hash chain value dynamic rotation and randomization mask technology; the Hash chain updating module iteratively updates the Hash chain value; the secure communication module adopts a lightweight encryption algorithm to protect communication data; and the system feedback optimization module dynamically adjusts the hash chain length and the key strength. The real-time performance and the anti-attack capability of the RFID system are remarkably improved, and a high-safety and low-power-consumption bidirectional authentication solution is provided for Internet of Things equipment.

The invention provides an identity recognition method and system based on unmanned aerial vehicle management and control. The method comprises the following steps: acquiring encrypted identity data based on unmanned aerial vehicle state monitoring, and generating an initial code containing a unique identifier, a position and a state parameter; dynamically adjusting a coding rule according to the acceleration variation, and generating a differential sequence matched with the motion state; generating a composite identifier containing a timestamp and a geo-fence through irreversible conversion; fusing the positioning data to dynamically bind the identifier and the track to generate synchronous track data; when the geofence is triggered, redundancy calibration is activated to generate anti-interference data; the composite identification and the anti-interference data are subjected to fragmentation packaging, and a topology dependence encryption block is constructed through a Hash abstract chain; and recombining the encrypted blocks in sequence based on the Hash chain, and checking the space-time consistency of the encrypted blocks and the geofence during recombining. According to the invention, the identity anti-counterfeiting and cross-region transmission security in the dynamic flight of the unmanned aerial vehicle is improved.

The invention discloses a corrugated carton production management system and method, and relates to the technical field of corrugated carton production, the system comprises a production scheduling module, a material tracing module, an equipment cooperation module, a multi-mode detection module and a cost control module, and solves the problem that supply and demand relationships, production efficiency and quality management and control are not coordinated; according to the technical key points, an order ID is coded into an integer chromosome, sequential crossover and reverse mutation operation are applied, a fuzzy comprehensive evaluation model is constructed by combining Hash chain table and local hill climbing method optimization, and factors are quantified through a trapezoidal membership function, so that the order delivery punctuality rate and the equipment utilization rate are improved, and the mold replacement cost is reduced; the real-time production cost is collected and calculated through Kafka and Flink, an operation cost method model is constructed to maintain a standard cost database, abnormity is detected through a CEP engine, the cost hyper-branched risk is predicted through an LSTM-Transform hybrid neural network, a thermodynamic diagram is generated through a cache result to assist decision making, the cost accounting delay time is shortened, and the hyper-branched processing efficiency is improved.

The invention provides an accident liability intelligent determination method and system fused with video tracking, and the method comprises the steps: S1, carrying out the alignment evidence collection of a video, an IMU, a GPS, and an OBD, and forming an evidence chain through framing Hash, chain Hash, and a timestamp; s2, completing detection segmentation on the shared trunk multi-branch network; s3, in combination with appearance re-identification and a motion model, realizing cross-frame association, and outputting track, speed and shielding recovery; s4, mapping the trajectory to BEV according to depth and calibration, and constructing a space-time scene graph by fusing lanes, signals, speed limit and the like; s5, extracting events such as lane changing, line merging and signal rushing, and positioning a conflict point and a way giving relation; s6, generating error factors according to a rule base and priority judgment; s7, quantifying the responsibility proportion according to the weight, the collision participation time and the reaction time; and S8, generating a report evidence of the key frame and the rule list. The system is composed of an acquisition evidence obtaining module, a video understanding tracking module, a space-time reconstruction module, an event extraction module, a rule reasoning module, a responsibility quantification module and a report evidence storage module.

Systems and processes are disclosed for a multidimensional, cross-node, hashchain, network-based Meta-Content Enabler (MCE) providing real time anomaly detection and impact analysis. Unique hexadecimal sequence identifiers are generated based on real time indexing and categorization to create a golden virtual metadata copy used by AI engine to determine content score to identify the degree of deviation therefrom, and to identify the hexadecimal nodes in the hashchain. The identified discrepancy is verified across cross-node hashchains to give end to end parallel impact analysis on the anomaly. By leveraging real-time monitoring, multidimensional verification, and blockchain-based storage, the system provides a robust and efficient solution for ensuring the accuracy and integrity of user activities. The system integrates privacy-preserving techniques, such as differential privacy or secure multi-party computation, to protect sensitive metadata. These techniques enable the system to analyze and process the metadata while preserving the privacy of individual users.

The invention discloses an intelligent system and method for fusing mental health evaluation in an interest scene based on an education robot. The system realizes non-intrusive mental health assessment by constructing a technical architecture of'multi-modal biological feature anonymization-quantum hybrid encryption-federated learning privacy protection-dynamic risk assessment '. The method is characterized by comprising the following steps of: (1) generating irreversible biological characteristic codes by adopting a chaos random number generator, and realizing anonymized association by combining a double hash chain technology; (2) designing a quantum enhanced hybrid encryption system, fusing an SM4 algorithm, NTRU post quantum cryptography and quantum key distribution; (3) developing a dynamic scene generator, and naturally fusing psychological test questions into interest topics by using a generative adversarial network (GAN) and a curiosity engine; (4) constructing a multi-modal emotion analysis system, and combining an LSTM + CNN hybrid model to realize physiology-behavior-voice data fusion analysis; and (5) deploying a federated learning framework, and protecting model training data through differential privacy noise injection (epsilon = 0.5).

The invention discloses an encryption protection method for network data backup and recovery, which relates to the technical field of data protection, and comprises the following steps: respectively implementing differential backup strategies by adopting a local, cloud and remote three-terminal collaborative backup architecture; and performing local data backup by a combined scheme of complete backup and incremental backup to generate a chained hash value sequence. Three-terminal key isolation and dynamic derivation are adopted to guarantee data security, an independent key system is adopted locally, cloud and remotely, a chain type key is generated locally based on a hash chain, version independent keys are generated at the cloud and remotely, and data security of other terminals is not affected by key leakage of any storage terminal. The recovery priority is automatically switched from local to cloud to remote, the local decrypts incremental data layer by layer through a hash chain, the cloud directly calls an independent key of a target version and uses a synthetic backup complete copy in remote, and the disaster recovery efficiency is improved through layered recovery and synthetic backup.

The invention discloses a dynamic business data updating and querying method and system, and particularly relates to the technical field of information processing, and the method comprises the following steps: S1, real-time data acquisition and preprocessing; s2, updating the dynamic data; s3, intelligent query optimization; s4, result feedback and visualization are carried out; and S5, performing anomaly detection and self-repairing. According to the method, the real-time processing capability and query efficiency of massive heterogeneous data are remarkably improved, the distributed sensor network is combined with lightweight encryption and a differential privacy mechanism to realize localized cleaning and feature extraction of multi-source data, the load of a central server is effectively reduced, and the risk of sensitive information leakage is avoided; an incremental synchronization mechanism depends on a message queue and Hash chain log technology to ensure the atomicity and traceability of data updating in a high-concurrency scene, and by combining a dynamically generated space-time multi-dimensional index and an adaptive weight distribution algorithm, the system can intelligently analyze query semantics and optimize path selection, and the response time of complex query is greatly shortened.

The invention provides a match alliance platform management system and method, and the system comprises a match authentication module constructed by a block chain, an AI-driven qualification auditing module, a process management module, a convolutional neural network, a big data analysis module, and an RBAC authority management module. Wherein the match authentication module dynamically analyzes and stores authenticated match rule data through an intelligent contract, and realizes rule version tracing by using an encrypted hash chain; the AI-driven qualification auditing module integrates a natural language processing engine to analyze the selection standard and construct a multi-dimensional evaluation model, and adopts a machine learning algorithm to analyze historical data of athletes to generate a visual qualification report; the process management module supported by cloud computing automatically generates an application process based on a rule engine, adopts a Monte Carlo algorithm to execute multi-constraint drawing, and constructs a directed graph model to dynamically generate a schedule topological structure containing a three-person rotation time sequence.

The invention relates to the technical field of road traffic safety and intelligent networking, in particular to a networking communication system for road traffic safety facilities. According to the system, a local traffic digital twinborn model is constructed by edge computing nodes and maintained in a federated synchronization mode; traffic data generated by an edge computing node is packaged in a data container with an embedded hash chain and a digital signature encryption traceability log, so that the integrity, primitiveness and traceability of the data are ensured; the vehicle-mounted terminal submits zero-knowledge proof as a service voucher, and the edge computing node verifies and authorizes the service on the premise of not obtaining the original sensitive data. According to the invention, efficient traffic state synchronization is realized by constructing the federated digital twinborn model, the credibility and safety of data exchange are guaranteed by using the data container, the terminal privacy is protected by means of the zero-knowledge proof technology, and the communication efficiency, the data safety and the privacy protection level of the vehicle-road cooperation system are comprehensively improved.

The invention discloses an ultrasonic water meter detection device and method, and relates to the technical field of ultrasonic flow metering, the device comprises an ultrasonic detection unit, a block chain evidence storage unit, a zero-knowledge proof module, a master control MCU and a low-power-consumption communication unit, the ultrasonic detection unit collects downstream and countercurrent ultrasonic propagation time difference delta t through symmetrically installed transducers, a time difference measurement module (precision + / -1ns) is combined with water temperature data to calibrate a delta t value, the block chain evidence storage unit constructs a Merkel tree for a delta t sequence according to a time window, and root hash is written into a private chain by improving a PBFT consensus mechanism (threshold 4 / 5 node confirmation). The method covers the whole process of data collection, evidence storage, verification and auditing, solves the problems that traditional water meter data is easy to tamper, privacy is leaked and installation is limited through a hash chain and zero-knowledge proof technology, and is suitable for an intelligent water affair scene.

The invention discloses a data index secure access method and related equipment, and relates to the technical field of data processing.The method comprises the steps that in response to a data access instruction, a dynamic index topological structure matched with a current network delay jitter value is generated based on a dynamic behavior fingerprint of a request terminal; performing real-time reconstruction on the dynamic index topological structure based on spatial and temporal distribution characteristics of the dynamic behavior fingerprints to generate an anti-collision verification path; a quantum noise signal is injected into the anti-collision verification path to form a cross-layer verification channel; performing asymmetric hash chain verification on the target data index through a cross-layer verification channel, and generating a verification result containing a fuzzy topology mark; performing dynamic remapping on the original index node according to the fuzzy topology mark, and outputting a security data index; and performing data access based on the secure data index. According to the method, the dynamicity, the unpredictability and the anti-analysis capability of the index path are realized, and the security and the anti-attack capability in the data access process can be comprehensively improved.

The invention discloses a self-adaptive multi-level digital watermarking method based on coding process optimization. The method comprises the following steps: firstly, performing deep preprocessing on an input video stream through a pre-trained multi-modal deep learning model, extracting space complexity, time dynamics and content significance features, and generating a uniform feature vector; and constructing a dynamic decision model based on the feature vectors, adaptively determining the watermark intensity, the embedding position and the type, and realizing accurate matching of watermark parameters and video content characteristics. A multi-level watermark hierarchical embedding mechanism is adopted, a robust invisible watermark, a fragile invisible watermark and a dynamic visible watermark are embedded into a video, and the security is enhanced by combining chaotic encryption or Hash chain encryption. During copyright verification, watermark information of each layer is recovered through an adaptive extraction algorithm, and data verification and infringement traceability are completed in combination with a block chain evidence storage system. According to the method, a full-process copyright protection system of embedding, coding, extraction and verification is constructed.

The invention relates to a dynamic double-layer hidden watermark and encryption binding file protection method and system based on deep learning, and belongs to the technical field of digital content security. The problems of attack resistance, traceability obstruction and key-watermark unhooking in document cross-platform circulation are solved. According to the scheme, the method comprises the following steps of: extracting semantic fingerprints by using a sentence vector model Sentence-BERT; the fuzzy extractor generates a master key and derives a time key chain; the authentication encryption algorithm AEAD encrypts and binds the source and the timestamp load; container layer structure rearrangement and document layer zero-width character double embedding are carried out; the generative adversarial network or diffusion model adversarial training improves the optical character recognition and transcoding resistance; version binding and tracing are achieved through the watermark hash chain. The technical effects cover anti-counterfeiting migration, cross-layer fault-tolerant guarantee recoverability, rearrangement attack resistance, full-period accurate traceability and post-quantum security enhancement.

The invention relates to the technical field of power equipment state monitoring and data security, and discloses a power equipment supply chain data sharing method based on a block chain, and the method comprises the following steps: S1, data collection and standardization: collecting sensor data of power equipment in real time, and carrying out the standardization processing; s2, dynamic entropy threshold calculation: dynamically calculating a data entropy threshold based on an information geometry theory; s3, verification mode decision making, wherein quantum chaos random walk data sampling or full-amount zero-knowledge proof verification is triggered according to entropy threshold decision making; and S4, anti-tamper certificate construction: constructing an anti-quantum hash chain for the sampled data and carrying out distributed anti-tamper coding. According to the method, through dynamic entropy threshold adaptation and quantum chaos sampling, accurate improvement of anomaly detection sensitivity is realized, based on Reed-Solomon fragmentation and algebraic verification, it is ensured that data can still be completely recovered when being partially tampered, and security and throughput efficiency are balanced by using block chain evidence storage and improvement of PBFT consensus.

A computer-implemented system for routing artificial intelligence (AI) queries. The system utilizes a zero-copy data pipeline, which processes prompts in memory-mapped buffers to eliminate at least one memory copy operation, thereby reducing latency relative to conventional serialization pipelines. The system continuously verifies AI provider compliance by injecting synthetic prompts containing invisible, Ed25519-signed Unicode watermarks. Algorithmic bias is detected by generating counterfactual “digital twin” prompts and applying Fisher exact statistical testing.Routing decisions for multi-tier autonomous systems are governed by safety-level requirements (ASIL-D, ASIL-B, QM) and may be constrained by external routing directives received via a meta-identifier. A hash-chained manifest, cryptographically signed using Ed25519 and consumed by downstream gateways, is generated for each routing decision, with its Merkle root asynchronously anchored to a blockchain to create a tamper-evident audit trail for regulatory compliance.

The invention belongs to the technical field of cross-border logistics information credibility management, and discloses a cross-border logistics information credibility management method based on block chain and dynamic hash chain evidence storage, and the method comprises the steps: deploying a multi-modal data adapter, integrating a lightweight MobileViT model and a category exclusive feature template, extracting a key frame through a video, and generating a feature package; after sensor data is subjected to Kalman filtering processing, a timestamp and a numerical sequence are output; a historical feature library is compared through an LSH algorithm, repeated features are filtered, evidence storage redundancy is avoided, unstructured data features are associated with structured data such as customs clearance numbers, accurate data correspondence during traceability is ensured, and a verification result is real and reliable; for a temporary checking scene, a temporary node generates a temporary permission containing a 24-hour validity period, and a corresponding Hash unit can only be verified and cannot be accessed after expiration, so that an illegal data access risk is completely eradicated, subsequent verification is prevented from being influenced by excessive permission recovery, and data security and credible verification requirements are balanced.

The invention discloses an automatic settlement path generation method fusing a knowledge graph and a tax rule, and relates to the technical field of financial science and technology and intelligent finance and tax compliance, and the method comprises the steps: S1, obtaining initial decision basis data and execution process details from a settlement path through a block chain network, employing a Hash chain structure to link each link record, s2, according to the obtained path chain, a graph database is adopted to store dynamic association attributes, and the dependency relationship of each node in the path is determined through knowledge graph reasoning, and S3, if an information fault is detected in the path chain, the matching degree of an execution result and a decision basis is compared through a timestamp verification mechanism, and if the information fault is detected in the path chain, the decision basis is determined. Judging a deviation position and marking a deviation point; according to the automatic settlement path generation method fusing the knowledge graph and the tax rules, the security and reliability of financial transactions and the tax management efficiency are effectively improved.

The invention discloses an archive information security storage and tamper-proof method and system based on a block chain, and belongs to the field of information security, the method comprises the following steps: obtaining archive information to be processed and generating standard archive data; a time sequence accumulation state hash model is adopted to process the standard archive data to generate digital fingerprints, and the time sequence accumulation state hash model constructs an academic state hash chain which takes initial academic state hash as a starting point and is recursively deduced along with time for each student; the generation of each new academic state hash is forced to depend on a previous academic state hash, a current period archive data abstract, a timestamp and a context challenge factor derived from a previous state; the digital fingerprints, the unique identity identifiers of the students and the operation metadata are packaged into archive information transactions, and the archive information transactions are signed by an authorization mechanism and then broadcasted to a block chain network; and a personal electronics file is formed. According to the invention, powerful and provable time sequence integrity is provided for auditing and tracing of archives.

The invention relates to the technical field of equipment management, and discloses a data security evidence storage method and system for smart city construction. The method comprises the following steps: acquiring operation state data of target equipment and performing encryption preprocessing to construct a security data set, further identifying data exception and determining a potential emergency list with relevance; equipment is intelligently grouped according to event priorities, a resource allocation scheme is generated and dynamically adjusted, and when the scheme does not meet the evidence storage requirement, standby resources are automatically obtained, and configuration is expanded; calculating and verifying a data storage path with the shortest delay by using a path selection model fusing bandwidth and priority constraints on the basis of an expansion scheme; and finally, carrying out full-link log recording on the evidence storage process along the path, implementing integrity verification based on a cryptographic hash chain, and carrying out closed-loop evaluation on a resource adjustment effect based on a verification result to generate a confirmation result. According to the invention, the timeliness and reliability of equipment data evidence storage in a complex environment of a smart city are improved.

The invention discloses a BIM and block chain-based construction whole process quality tracing method and system, and relates to the technical field of building construction quality management. In a material entering stage, material information is collected through the Internet of Things and is associated with a BIM component identifier, and an initial block is generated by using an intelligent contract; in the process execution stage, BIM 4D / 5D simulation data is associated with a construction log, and a Hash chain algorithm is adopted to generate a process block containing IPFS Hash; in the acceptance inspection stage, the consistency of detection results is verified through zero-knowledge proof, and a new block is generated; checking the block data through a consensus mechanism to obtain a complete data set; constructing a graph database index based on the BIM component tree, and generating a chain path graph; responding to a query request, traversing path diagram nodes, comparing hash values and outputting a tracing result; trusted communication, tamper-proof evidence storage and intelligent tracing of data in the whole construction process are achieved, and the accuracy and reliability of project quality management are remarkably improved.

The invention belongs to the field of engineering management, and particularly relates to an electric power project full life cycle management method and system based on digital twinning, so as to solve the technical problems that digital twinning and a construction plan are disjointed, and a risk assessment and permanent data capitalization mechanism driven by real-time data is lacked. Obtaining a construction plan of the task unit and a digital twinborn model; s2, establishing an association relationship between a task unit and a component; s3, calculating a vector deviation between a field entity state and a digital twin model target state; calculating a risk coefficient of the component; forming a dynamic construction plan; and S4, performing structured packaging and Hash linking on the vector deviation, the risk coefficient, the quality acceptance result and the resource consumption data, and generating construction process data bound with the component. The defect of disjunction of plans and models in traditional management is overcome, possible space and resource conflicts in the future can be pre-judged and avoided, and the integrity and authenticity of process data are ensured.

The invention provides a warehouse receipt supervision method and platform based on the Internet of Things, and relates to the technical field of warehouse management, and the method comprises the following steps: deploying an Internet of Things device in a warehouse, collecting the state information of stored goods in real time, preprocessing the collected data, and generating a warehouse receipt; generating a unique initial hash value for each warehouse receipt, and combining the warehouse receipt with the current hash value when a new warehouse receipt is generated each time; the Internet of Things equipment is deployed in the warehouse, the state information of the stored goods is collected in real time, the warehouse receipt is generated, the warehouse receipt information is processed and verified in real time through cooperation of the dynamic hash chain algorithm and the block chain, and then the warehouse receipt information is stored in the block chain, so that the authenticity and integrity of data are ensured, and the storage efficiency is improved. Verification rules and business logic of warehouse receipt information can be defined through an automatic algorithm, data verification and updating operation can be automatically executed, follow-up query, monitoring and auditing are facilitated, the whole supervision process is matched with automatic operation of the algorithm, and a large amount of manpower, material resources and financial resources are saved.

The invention belongs to the technical field of artificial intelligence computing and scheduling, and particularly relates to a distributed intelligent computing resource scheduling optimization method and system, and the method comprises the steps: obtaining and registering the computing task information sent by each user node in real time, and recording the task information to a block chain; state information of computing resources of the intelligent computing center nodes is collected and registered in real time, and the state information of the computing resources is recorded to the block chain; in combination with the task information of the real-time user node and the state information of the computing resources of the intelligent computing center node, reasoning an optimal scheduling strategy by using a reinforcement learning algorithm to obtain an optimal scheduling node, and recording the optimal scheduling node to the block chain; scheduling the task to the optimal scheduling node by using the optimal scheduling strategy, locking resources, triggering task execution, and recording a task execution result to the block chain; and constructing and verifying a hash chain based on a task execution process, and updating the reputation of a task execution node in real time based on a verification result to form a closed-loop reward mechanism.

A method for auditable off-chain transaction in block-chain network includes: defining counterparties, auditors and their responsibilities; creating an off-chain payment channel between the counterparties and initializing the off-chain payment channel by both of the counterparties; updating channel status during each transaction process; and initiating an audit process to verify an integrity of a history of the off-chain transaction after the off-chain payment channel is closed; wherein a hash chain linking current and previous transactions of the off-chain payment channel in a chronological order is established during the transaction processes, and an Accountable Assertions with Flexible Public Key (AAFPK) mechanism is used to bind fund and commitment information generated by counterparties to a flexible public key through assertions, the hash chain is submitted to auditors for verifying when off-chain payment channel is closed, and AAFPK mechanism binds inconsistencies or differences of the off-chain transaction to a responsible party.

An example operation may include one or more of receiving, at a data provider, a data file from a data modifier which comprises a modification to an initial content state of a data file, generating a hash value of the initial content state of the data file prior to modification and generating a hash value of a modified content state of the data file after the modification, and transmitting the generated hash values to a blockchain peer node for inclusion within one or more data blocks among a hash-linked chain of data blocks.

The invention relates to the technical field of image detection, can be applied to a financial science and technology business system platform, and discloses a tamper-proof loss assessment image traceability method, device, equipment and medium, and the method comprises the steps: obtaining global positioning data, base station positioning data and equipment sensor data of a loss assessment image; performing fusion processing on the global positioning data, the base station positioning data and the equipment sensor data to obtain a dynamic timestamp; a preset device hardware fingerprint and a preset sensor fingerprint are combined to generate a composite fingerprint; performing asymmetric encryption binding on the dynamic timestamp and the composite fingerprint to obtain encryption binding data; performing multiple hash processing on the loss assessment image to obtain hash chain data; and tracing the loss assessment image according to the encrypted binding data and the Hash chain data to obtain a tracing result. Through traceability of shooting information, the phenomenon that the operator does not arrive at the scene for survey and certificate collection and is shot by others can be avoided, the leakage risk of a case is further reduced, and the operation cost of a company is reduced.