A data desensitization method based on logback log component

Abstract

The invention discloses a data desensitization method based on a Logback log component, and belongs to the technical field of data desensitization. The invention includes: 1. Loading configuration information when the business system is started; 2. Using a message converter to intercept the original log data; 3. Detecting the original log data, obtaining fields and data values ​​that meet desensitization rules, and classifying them; 4. According to the desensitization rule type configured in the Java annotation or according to the desensitization rule type corresponding to the field, query the desensitization rule and desensitize the data value; 5. Output the desensitized data to the log output component of Logback and output log files. Based on the Logback log component, the present invention combines the built-in global desensitization field and the configuration of Java annotations to desensitize private data, solves the problem of private data exposure in various business scenarios, and has high operating efficiency and strong scalability , low cost and good compatibility.

Description

technical field [0001] The invention belongs to the technical field of data desensitization, and in particular relates to a data desensitization method based on a Logback log component. Background technique [0002] Business systems in the financial industry usually involve the collection and processing of private data such as customer names, ID numbers, bank card numbers, mobile phone numbers, and passwords. If these data are directly recorded in the system log, improper management will result in loss of customer privacy data. Leakage, and doing so does not meet the regulatory requirements of the financial regulatory authorities, and cannot meet data compliance. [0003] Data desensitization is a method of transforming private data using given desensitization rules and strategies to protect private data security; desensitizing business system logs can effectively reduce customer privacy data leakage, Improve the level of data protection, meet data compliance, and implement...

AI Technical Summary

Problems solved by technology

However, Scheme 2 mainly has the following problems: 1. The data desensitization component needs to intercept and detect all log data, which has a large data range and low processing efficiency; 2. It can only process private data in a specific format (such as mobile phone number), Formatted data (such as passwords) can't do anything

Solution 3 only needs to intercept the predefined key in the log data and process the data corresponding to the value. Compared with solution 2, the scope of data processing is reduced and the efficiency is improved, but there are still the following problems: 1. Lack of flexibility, if because If you need to change the name of the key or change the desensitization rules of the value for business reasons, you need to modify the data desensitization component; 2. The scope of application is narrow. For multiple business scenarios, the key of private data is the same, but the value needs to use different desensitization rules. deal with the scene, there is nothing you can do

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