CN-121984768-A - Encryption storage method and system for distributed data element clusters

Abstract

The invention relates to the technical field of data processing, in particular to an encryption storage method and system for a distributed data element cluster. The method comprises the steps of obtaining cluster characteristics of a data element cluster, node access data and attack flow data of each distributed storage node, carrying out characteristic value evaluation on single data elements in the cluster characteristics to obtain substitution trend degree and value-added reflection degree of the data elements, combining the substitution trend degree, the value-added reflection degree and the node access data, calculating storage display degree on each storage node, carrying out fluctuation feature analysis on the attack flow data to obtain storage risk degree on each storage node, carrying out encryption demand analysis on each type of data elements to obtain corresponding encryption demand degree by integrating the storage display degree and the storage risk degree, and carrying out encryption processing of corresponding intensity levels on each type of data elements in the data element cluster according to each encryption demand degree to realize accurate encryption storage of data elements with different information value differences.

Inventors

• Gao Houliang
• WANG SUDONG
• CUI YANLI

Assignees

• 中投国信(北京)科技发展有限公司

Dates

Publication Date

20260505

Application Date

20260211

Claims (10)

1. 1. A method of encrypted storage of a distributed data element cluster, the method comprising: Acquiring cluster characteristics of a data element cluster, node access data of each distributed storage node and attack flow data; evaluating the single element feature value of the cluster feature in the time sequence dimension to obtain the substitution trend degree and the increment reflection degree of the data elements corresponding to the data element cluster; calculating the storage showing degree of the data element cluster in each storage node according to the substitution trend degree, the value-added reflection degree and the node access data; analyzing the fluctuation characteristics of the attack flow data to obtain the storage risk degree of the data element cluster in each storage node; Carrying out encryption requirement analysis on each type of data elements according to the storage display degree and the storage risk degree to obtain encryption requirement degrees of various types of data elements; and encrypting various data elements of the data element cluster according to each encryption requirement degree to corresponding intensity levels.
2. 2. The method for encrypting and storing a distributed data element cluster according to claim 1, wherein said evaluating the individual element feature values of the cluster features in the time-series dimension to obtain the substitution tendencies and the added value reflectances of the data elements corresponding to the data element cluster comprises: obtaining element slopes of corresponding class data elements according to a storage time sequence curve of each class of element features in the cluster features, wherein the storage time sequence curve is a curve of the storage times of the element features changing along with the duration of a storage interval; Obtaining the substitution trend degree of the corresponding data elements according to the element slope and the storage time length mean value of each type of data elements; And carrying out feature analysis on the access times of each type of element features in the cluster features to obtain the value-added reflection degree of the corresponding data elements.
3. 3. The method for encrypting and storing the distributed data element cluster according to claim 2, wherein the performing feature analysis on the number of accesses of each type of element feature in the cluster feature to obtain the value-added reflection degree of the corresponding data element comprises: Obtaining a first access proportion of the current category element features according to a first total access frequency of the current category element features and a first maximum access frequency of the category element features in the cluster features; Obtaining a second access proportion of the maximum access element feature according to the second total access times of all category element features in the cluster feature and the second maximum access times of all element features; And obtaining the value-added reflecting degree of the element characteristics of the current category according to the first access proportion and the second access proportion.
4. 4. The method according to claim 1, wherein calculating a storage representation of the data element cluster in each storage node according to the substitution trend, the value-added reflection and the node access data comprises: according to the substitution trend and the increment reflection degree of the data elements of the same category, obtaining the value measurement coefficient of the data elements of the corresponding category; Extracting node access times of the current node from the node access data, and calculating historical access means of all the nodes; And obtaining the storage showing degree of the data element cluster in each storage node according to the value measurement coefficient, the node access times and the historical access mean value.
5. 5. The method for encrypting and storing a distributed data element cluster according to claim 1, wherein analyzing the fluctuation feature of the attack traffic data to obtain the storage risk of the data element cluster in each storage node comprises: Carrying out fluctuation feature analysis on attack flow data of each distributed storage node to obtain attack presentation degree of each storage node; and carrying out statistical analysis on the attack presentation degree of each storage node to obtain the storage risk degree of the data element cluster.
6. 6. The method for encrypting and storing a distributed data element cluster according to claim 5, wherein the performing the fluctuation feature analysis on the attack traffic data of each distributed storage node to obtain the attack rendering degree of each storage node comprises: obtaining a maximum access proportion according to the total access flow of all the storage nodes and the maximum access flow in the current storage node; and obtaining the attack presentation degree of the current storage node according to the maximum access proportion and the flow curve slope of the current storage node.
7. 7. The method for encrypting and storing a distributed data element cluster according to claim 5, wherein said performing a statistical analysis on attack presentities of the storage nodes to obtain a storage risk of the data element cluster comprises: Counting the average value of all attack presentation degrees in the same time period to obtain the attack degree average value of each storage node; Counting the difference value of attack presentation degrees between adjacent storage nodes in the same period, taking absolute value, and then averaging to obtain an average attack degree difference value; And obtaining the storage risk degree of the data element cluster according to the attack degree mean value and the average attack degree difference value.
8. 8. The method for encrypting and storing a distributed data element cluster according to claim 1, wherein the step of analyzing the encryption requirement of each type of data element according to the storage showing degree and the storage risk degree to obtain the encryption requirement degree of each type of data element comprises the following steps: Obtaining the actual display degree of the current storage node according to the current storage display degree of the current storage node, the average storage display degree of all the storage nodes and a preset amplitude adjustment coefficient; and obtaining the encryption demand degree of the corresponding category data elements in the current storage node according to the actual display degree of the current storage node and the storage risk degree.
9. 9. The method for encrypting and storing a distributed data element cluster according to claim 1, wherein said encrypting each type of data element of said data element cluster to a corresponding intensity level according to each encryption requirement comprises: converting each encryption demand into a corresponding intensity level according to the preset encryption level number; And sequentially performing fragmentation processing and hash value calculation on the data elements according to the intensity level, and distributing the data elements to the selected storage nodes through a point-to-point network.
10. 10. An encrypted storage system for a distributed data element cluster, characterized in that it is adapted to store the distributed data element cluster in an encrypted manner by the method according to any one of claims 1 to 9, said system comprising: The acquisition module is used for acquiring cluster characteristics of the data element clusters, node access data of each distributed storage node and attack flow data; the first obtaining module is used for evaluating the single element feature value of the cluster feature in the time sequence dimension and obtaining the substitution trend degree and the increment reflection degree of the data elements corresponding to the data element cluster; The processing module is used for calculating the storage showing degree of the data element cluster in each storage node according to the substitution trend degree, the value-added reflection degree and the node access data; the second obtaining module is used for analyzing the fluctuation characteristics of the attack flow data and obtaining the storage risk degree of the data element cluster in each storage node; The third obtaining module is used for carrying out encryption requirement analysis on each type of data elements according to the storage display degree and the storage risk degree to obtain the encryption requirement degree of each type of data elements; And the encryption module is used for encrypting various data elements of the data element cluster to corresponding intensity levels according to each encryption requirement degree.

Description

Encryption storage method and system for distributed data element clusters Technical Field The invention relates to the technical field of data processing, in particular to an encryption storage method and system for a distributed data element cluster. Background The data elements are data resources which exist in an electronic form, participate in production operation and exert value through calculation, the distributed data element cluster takes a distributed architecture as a core, the storage, processing, circulation and application functions of the data elements are distributed and deployed on a plurality of independent storage nodes, and novel data management ecology of data sharing, task coordination and value release among the nodes is realized through a standardized protocol and a coordination mechanism. The distributed encryption storage is carried out on each data element cluster by the block chain technology to improve the security storage level of data, encryption algorithm is adopted to encrypt the data element clusters before the data information is stored, and AES (Advanced Encryption Standard ‌, advanced encryption standard) is adopted for symmetric encryption in the traditional method, wherein the encryption intensity level of each data element information is a preset fixed value, and the encrypted ciphertext is subjected to the block chain storage. However, in an actual scene, the information values of the data element information in different clusters are different, and the encryption processing of the data elements with different security levels cannot be applied by adopting a fixed encryption intensity level in the prior art. Disclosure of Invention In order to solve the technical problem of how to improve the accuracy of encryption processing of data elements under different information value differences, the invention aims to provide an encryption storage method and system for a distributed data element cluster, and the adopted technical scheme is as follows: in a first aspect, an embodiment of the present invention provides an encryption storage method for a distributed data element cluster, where the method includes: Acquiring cluster characteristics of a data element cluster, node access data of each distributed storage node and attack flow data; Evaluating the single element feature value of the cluster feature in the time sequence dimension to obtain the substitution trend degree and the increment reflection degree of the data element corresponding to the data element cluster; calculating the storage showing degree of the data element clusters in each storage node according to the substitution trend degree, the value-added reflection degree and the node access data; Analyzing fluctuation characteristics of attack flow data to obtain storage risk degrees of the data element clusters in all storage nodes; Carrying out encryption demand analysis on each type of data elements according to the storage display degree and the storage risk degree to obtain the encryption demand degree of each type of data elements; and encrypting various data elements of the data element clusters according to each encryption requirement degree to corresponding intensity levels. In an alternative embodiment, evaluating individual element feature values of the cluster features in a time-series dimension to obtain a surrogate trend and a value-added reflection of corresponding data elements of the cluster of data elements, comprising: Obtaining element slopes of corresponding class data elements according to a storage time sequence curve of each class of element features in the cluster features, wherein the storage time sequence curve is a curve of the storage times of the element features changing along with the duration of a storage interval; Obtaining the substitution trend degree of the corresponding data elements according to the element slope and the storage time length mean value of each type of data elements; And carrying out feature analysis on the access times of each type of element features in the cluster features to obtain the value-added reflecting degree of the corresponding data elements. In an alternative embodiment, performing feature analysis on the access times of each class of element features in the cluster features to obtain the value-added reflection degree of the corresponding data elements, including: Obtaining a first access proportion of the current category element features according to a first total access frequency of the current category element features and a first maximum access frequency of the category element features in the cluster features; obtaining a second access proportion of the maximum access element feature according to the second total access times of all category element features in the cluster feature and the second maximum access times of all element features; and obtaining the value-added reflecting degree of the current category element characteristics ac