Desensitization system and desensitization method used for big data

Abstract

The invention discloses a desensitization system used for big data. The desensitization system comprises a database type management module, a system management module, a data source management module, a sensitive data discovery module, a desensitization task management module, a desensitization configuration management module, a multi-stage management module, a big data desensitization analysis module and a sensitive data classification module, wherein the database type management module manages the type of desensitization data; the system management module constructs a role for a desensitization system and carries out function authorization and management on the role; the data source management module provides data source management for the desensitization system; the sensitive data discovery module automatically discovers the sensitive data in the data source and submits the sensitive data to the user for regulation and confirmation; the desensitization task management module configures and manages the desensitization task of a big data desensitization system; the desensitization configuration management module manages and defines the sensitive data and carries out desensitization algorithm and desensitization strategy management; the multi-stage management module realizes the state monitoring, the strategy issuing and the data synchronization of multi-stage desensitization equipment; the big data desensitization analysis module carries out real-time analysis on collected desensitization log data to guarantee the security of the desensitization system; and the sensitive data classification module carries out characteristic analysis on the sensitive data to classify the sensitive data. The invention also discloses a desensitization method used for the big data.

Description

technical field [0001] The present invention relates to the cross technical field of computer technology and information security, in particular, the present invention relates to a desensitization system and desensitization method for big data. Background technique [0002] The Internet security situation in the era of big data has also gradually changed, and information security has risen to the height of national strategy. The Outline of the Thirteenth Five-Year Plan for National Economic and Social Development of the People's Republic of China puts forward: "implement the national big data strategy and promote the opening and sharing of data resources". However, data resources contain a large amount of sensitive and important information, and the current laws and regulations on the protection of sensitive and private data are not perfect. Once sensitive information is leaked or illegally used, it will bring irreparable losses to individuals and even the country. By desen...

AI Technical Summary

Problems solved by technology

[0008] 1. Data resources include structured, semi-structured and unstructured data types. At present, most data research only focuses on structured database data. How to desensitize sensitive data of pictures, files and multimedia (video, audio) Still in the exploratory stage, there is no mature method and process

[0009] 2. Most of the existing sensitive data identification methods are based on rule discovery and manual definition. The rule-based discovery method can effectively identify sensitive data that conforms to the rule definition, but it will miss a large number of irregular sensitive data, reducing the sensitivity of sensitive data identification. Accuracy; on the other hand, when the amount of data is relatively large, the method based on manual definition will increase the burden on users and reduce the usability and ease of use of the system

[0010] 3. Existing data desensitization only considers the identification of sensitive data of a single node, ignoring the issues of sensitive data desensitization and supervision of multi-level departments

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