CN-122018793-A - Cross-organization data storage method and system based on blockchain intelligent contract

CN122018793ACN 122018793 ACN122018793 ACN 122018793ACN-122018793-A

Abstract

The application provides a cross-mechanism data storage method and system based on a blockchain intelligent contract, and relates to the technical field of data storage, wherein the method comprises the steps of firstly collecting three-dimensional shape data of a data storage entity surface, generating enhanced characteristic data by enhancing characteristic contrast through coherent light processing, then performing compression coding and baseline drift elimination by adopting pulse width modulation, performing hash operation on a processed pulse sequence to generate a characteristic hash value, and storing the characteristic hash value and original data together into a cross-mechanism blockchain; when an organization initiates a data reading request, triggering a verification process through an intelligent contract, comparing the matching degree of the real-time hash value and the stored hash value, triggering a warning mechanism and broadcasting an abnormal event to the whole network if the matching degree exceeds the tolerance range, and recording abnormal information into a block chain non-tamperable log. The application improves the tamper resistance of the cross-institution data storage and the reliability of entity identity verification.

Inventors

XIA MEI
MA ZHAOQING
FENG YINGZHI

Assignees

职豆豆(南京)信息技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260120

Claims (10)

1. A blockchain smart contract-based cross-organization data storage method, comprising: Collecting original data of a data storage entity and three-dimensional morphology data of the surface of the data storage entity, wherein the original data and the three-dimensional morphology data are transferred among multiple mechanisms; performing enhancement processing on the three-dimensional morphology data by adopting a coherent light processing method to generate enhancement characteristic data; performing compression coding processing on the enhancement characteristic data by adopting a pulse width modulation mode, generating a compressed pulse sequence, and performing elimination processing on the compressed pulse sequence; performing hash operation on the compressed pulse sequence after the elimination processing to generate a characteristic hash value, and storing the characteristic hash value and the original data together into a cross-mechanism block chain; based on an intelligent contract, combining stored data of a cross-mechanism blockchain, when any mechanism initiates a data reading request, executing a verification process to generate a real-time hash value, and matching the real-time hash value with a characteristic hash value stored in the cross-mechanism blockchain through the intelligent contract; when the matching result does not meet the preset tolerance requirement, triggering a warning mechanism of the intelligent contract, broadcasting an abnormal event to all mechanism nodes in the cross-mechanism blockchain, and simultaneously storing identification information, time stamps and characteristic deviation data of the abnormal mechanism nodes into a distributed non-tamperable log of the cross-mechanism blockchain.
2. The method of claim 1, wherein the performing a verification process to generate a real-time hash value when any of the institutions initiates a data read request based on the smart contract in conjunction with the stored data across the institution blockchain, the matching the real-time hash value with the characteristic hash value stored across the institution blockchain by the smart contract comprises: In the intelligent contract, establishing a verification relationship based on the corresponding relationship between the characteristic hash value and stored data of the cross-organization blockchain; Based on the verification relation, when any mechanism initiates a data reading request, the intelligent contract automatically triggers a feature acquisition instruction, and based on the feature acquisition instruction, optical feature data of the surface of the current data storage entity are acquired; Generating a real-time hash value based on the optical characteristic data; and carrying out bit-by-bit comparison and difference analysis on the real-time hash value and the characteristic hash value stored in the blockchain by using a similarity calculation algorithm through a verification execution module of the intelligent contract so as to obtain a matching result.
3. The method according to claim 2, wherein the performing a bit-by-bit comparison and a variance analysis on the real-time hash value and a characteristic hash value stored in a blockchain by using a similarity calculation algorithm to obtain a matching result includes: Calculating the Hamming distance of the bit corresponding to the real-time hash value and the characteristic hash value stored in the blockchain, and taking the Hamming distance as a difference index; A sliding window algorithm is adopted to conduct segment comparison on the real-time hash value and the characteristic hash value stored in the blockchain so as to identify a local distribution mode; Analyzing the local distribution pattern, and detecting deviation characteristics; and comprehensively analyzing the deviation features, the difference index and the local distribution mode to generate a comprehensive matching degree score, wherein the comprehensive matching degree score is a matching result.
4. The method of claim 1, wherein the enhancing the three-dimensional topography data using a coherent light processing method to generate enhanced feature data comprises: Illuminating the surface of the data storage entity through a coherent light source to generate an interference fringe pattern, and recording brightness distribution data of the interference fringe pattern; performing phase-shift interference processing on the brightness distribution data to generate a phase-shift interference pattern; extracting phase information from the phase-shift interferogram by a phase resolving algorithm, and generating a phase modulation distribution diagram based on the phase information; and carrying out fusion processing on the phase modulation distribution diagram and the three-dimensional morphology data, and generating enhanced characteristic data by adopting a weighted superposition algorithm.
5. The method of claim 4, wherein the fusing the phase modulation profile with the three-dimensional topography data to generate enhanced feature data using a weighted overlap-add algorithm comprises: Calculating a corresponding self-adaptive weight coefficient according to the phase gradient value of each pixel point in the phase modulation distribution diagram; According to the self-adaptive weight coefficient, carrying out pixel-by-pixel fusion calculation on the depth information of the three-dimensional morphology data and the phase information of the phase modulation distribution diagram by adopting a weighted superposition algorithm to generate preliminary optical characteristic data; Performing edge optimization processing on the preliminary optical characteristic data by adopting an anisotropic diffusion filtering algorithm to obtain intermediate optical characteristic data; and performing contrast enhancement and dynamic range adjustment on the intermediate optical characteristic data to generate enhancement characteristic data.
6. The method of claim 1, wherein the performing a compression encoding process on the enhancement feature data using a pulse width modulation method to generate a compressed pulse sequence, and performing a cancellation process on the compressed pulse sequence, comprises: dynamically adjusting pulse modulation parameters according to the data characteristics of the enhancement characteristic data; Based on the adjusted pulse modulation parameters, the enhancement characteristic data are segmented according to the size of a preset data block, and each data block is converted into a modulation signal with specific pulse width and pulse interval through a pulse width modulation mode; Performing differential Manchester encoding on all the modulation signals to generate a compressed pulse sequence; And carrying out elimination treatment on the compressed pulse sequence by adopting an adaptive baseline correction technology to obtain an eliminated compressed pulse sequence.
7. The method of claim 1, wherein hashing the compressed pulse sequence after the cancellation process to generate a characteristic hash value comprises: performing multiple iterations through a compression function, performing grouping processing on the compressed pulse sequence after the elimination processing, performing bit rotation, modulo addition operation and nonlinear logic function operation in each iteration round, and converting the compressed pulse sequence after the elimination processing into an intermediate hash value with a fixed length; inputting the intermediate hash value into a deep hash neural network, and performing feature enhancement processing on the intermediate hash value through a multi-layer perceptron module in the deep hash neural network to obtain a target hash value; and combining the target hash values of the packets through a cascade processing module in the deep hash neural network to generate a characteristic hash value.
8. A blockchain smart contract-based cross-institution data storage system, comprising: The acquisition module is used for acquiring original data of the data storage entities and three-dimensional morphology data of the surfaces of the data storage entities, wherein the original data and the three-dimensional morphology data are transferred among the multiple mechanisms; The enhancement module is used for enhancing the three-dimensional morphology data by adopting a coherent light processing method to generate enhancement characteristic data; The coding module is used for carrying out compression coding processing on the enhancement characteristic data by adopting a pulse width modulation mode, generating a compressed pulse sequence and carrying out elimination processing on the compressed pulse sequence; the generation module is used for carrying out hash operation on the compressed pulse sequence after the elimination processing, generating a characteristic hash value and storing the characteristic hash value and the original data together into a cross-mechanism block chain; The execution module is used for combining stored data of the cross-mechanism blockchain based on an intelligent contract, executing a verification process when any mechanism initiates a data reading request to generate a real-time hash value, and matching the real-time hash value with a characteristic hash value stored in the cross-mechanism blockchain through the intelligent contract; And the triggering module is used for triggering a warning mechanism of the intelligent contract and broadcasting an abnormal event to all mechanism nodes in the cross-mechanism blockchain when the matching result does not meet the preset tolerance requirement, and simultaneously storing identification information, time stamp and characteristic deviation data of the abnormal mechanism nodes into a distributed non-tamperable log of the cross-mechanism blockchain.
9. An electronic device, comprising: A memory for storing a computer program; A processor for implementing the steps of the blockchain smart contract-based cross-organization data storage method of any of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, the computer program when executed by a processor is capable of implementing the blockchain smart contract-based cross-organization data storage method of any of claims 1 to 7.

Description

Cross-organization data storage method and system based on blockchain intelligent contract Technical Field The application relates to the technical field of data storage, in particular to a cross-mechanism data storage method and system based on a blockchain intelligent contract. Background In the scene of cross-border logistics and the like requiring the cooperative operation of a plurality of institutions, each participant must ensure that an unique and stable binding relation exists between an important data entity and corresponding digital information and realize the trusted transfer of the important data entity in the whole chain, therefore, the scene has specific requirements on a data storage mode, namely the scene must have the capabilities of tamper resistance, traceability and real-time verification among a plurality of institutions, and meanwhile, a bidirectional verification mechanism between a physical entity and a digital identity is also required to be supported, so that the problems of authenticity and consistency possibly occurring in the process of multiparty transfer of data are effectively solved. At present, a targeted solution exists, the solution adopts a distributed database and combines a digital label technology, a unique radio frequency identification label is allocated to each entity article, the label number and the complete information of the article are associated and stored in a shared database, a participating mechanism scans the radio frequency identification label of the entity article through a reader-writer to acquire the number, then the shared database is queried to verify whether the acquired article information is consistent with records, and the records of all the operations are synchronized to each participating node through a consensus mechanism. However, the scheme has a certain limitation in terms of physical characteristic acquisition, because the scheme relies on pre-attached label media, and the binding relationship between an object and digital information is easily damaged due to physical damage in practical application, and meanwhile, the verification process is mainly concentrated on matching of label numbers, and direct sensing and comparison of physical characteristics of the entity object are lacked, so that the risk that the label is true but the attached entity object is replaced is brought. In addition, the support of the existing method for the multi-mechanism collaborative verification scene is single, and the direct perception of the entity characteristics and the distributed consensus mechanism cannot be deeply fused, so that the requirement for tamper resistance in the high-security-level scene is difficult to meet. Disclosure of Invention The application provides a cross-organization data storage method and system based on a blockchain intelligent contract, which are used for solving the problems of low tamper resistance of the cross-organization data storage and poor reliability of entity identity verification in the prior art. In order to solve the technical problems, in a first aspect, the present application provides a cross-mechanism data storage method based on a blockchain intelligent contract, including: Collecting original data of a data storage entity and three-dimensional morphology data of the surface of the data storage entity, wherein the original data and the three-dimensional morphology data are transferred among multiple mechanisms; performing enhancement processing on the three-dimensional morphology data by adopting a coherent light processing method to generate enhancement characteristic data; performing compression coding processing on the enhancement characteristic data by adopting a pulse width modulation mode, generating a compressed pulse sequence, and performing elimination processing on the compressed pulse sequence; performing hash operation on the compressed pulse sequence after the elimination processing to generate a characteristic hash value, and storing the characteristic hash value and the original data together into a cross-mechanism block chain; based on an intelligent contract, combining stored data of a cross-mechanism blockchain, when any mechanism initiates a data reading request, executing a verification process to generate a real-time hash value, and matching the real-time hash value with a characteristic hash value stored in the cross-mechanism blockchain through the intelligent contract; when the matching result does not meet the preset tolerance requirement, triggering a warning mechanism of the intelligent contract, broadcasting an abnormal event to all mechanism nodes in the cross-mechanism blockchain, and simultaneously storing identification information, time stamps and characteristic deviation data of the abnormal mechanism nodes into a distributed non-tamperable log of the cross-mechanism blockchain. Optionally, when any organization initiates a data reading request, the verifying process is e