Cache data desensitization in Java caching technology

With the increasing popularity of Internet applications and the rapid growth of data volume, more and more applications are beginning to use caching to improve performance and reduce system load. In Java caching technology, data security is a very important issue, especially in some scenarios where user privacy needs to be protected, such as finance, medical care, e-commerce, etc. A common data security requirement is cache data desensitization. This article will introduce in detail the cache data desensitization strategy in Java caching technology.

1. The concept of cache data desensitization

Cache data desensitization refers to an operation that processes sensitive data and replaces it with forged data that does not contain sensitive information. This operation can effectively protect the security of real data and ensure that sensitive data will not be leaked. At the same time, important information such as data structure and data type is retained, so that the application system can run normally. Common cache data desensitization methods include the following:

1. Data desensitization algorithm

The data desensitization algorithm converts original sensitive information by encrypting and decrypting sensitive data. into forged data, thereby achieving data desensitization. Common data desensitization algorithms include MD5 encryption algorithm, SHA1 algorithm, AES encryption algorithm, etc. These algorithms need to be pre-defined in the application, and different algorithms can be used for encryption according to different situations.

2. Data desensitization rules

Data desensitization rules refer to data desensitization rules defined according to business needs. Sensitive data is processed through specific rules to achieve data desensitization. . Common data desensitization rules are as follows:

① Character data desensitization

Character data desensitization refers to processing sensitive data of text type, usually by converting characters The string is randomly shuffled or replaced with "*" for processing.

②. Date type data desensitization

Date type data desensitization refers to processing sensitive data of date type, usually by converting the date into a common format, such as: converting "2021- 05-13" is converted to "yyyy-MM-dd" for processing.

③. Numerical data desensitization

Numerical data desensitization refers to the processing of sensitive data of numerical type, usually by rounding and rounding the numbers.

2. Data desensitization in Java cache technology

Java cache technology mainly includes Ehcache, Redis, Caffeine, Guava Cache and other implementation methods. Among them, Ehcache is an open source Java cache framework that supports distributed cache, local cache, expiration time and other functions; Redis is a high-performance database cache middleware that supports diversified cache data types and has in-memory database features; Caffeine and Guava Cache, both from Google, are two Java-based local cache implementations.

In Java caching technology, data desensitization mainly deals with scenarios where sensitive data exists in the cache. How to desensitize cached data must not only consider data security, but also ensure the efficiency and availability of cache operations. The specific implementation method is as follows:

1. Use the interceptor of the cache framework for processing

Implementation approach: You can modify the source code of cache frameworks such as Ehcache and Redis, and use interceptors to cache data intercept and process.

Workflow: When a user requests cached data, the data interceptor will first read the data, then desensitize the sensitive data according to the rules, and finally return it to the user.

Advantages: The operation is simple and only needs to modify the source code of the framework to achieve it, with less impact on the business code.

Disadvantages: The framework source code needs to be modified, which is not conducive to upgrade and maintenance.

2. Use the tool classes provided by the cache framework for processing

Implementation approach: You can use the tool classes provided by cache frameworks such as Ehcache and Redis to encrypt cached data.

Workflow: When a user requests cached data, the tool class will first read the data, then encrypt the sensitive data according to the rules, and finally return it to the user.

Advantages: No need to modify the framework source code, easy to operate, easy to maintain and manage.

Disadvantages: The cached data needs to be encrypted and decrypted, which may affect the efficiency and performance of the operation.

3. Suggestions for data desensitization

In Java cache technology, cache data desensitization is a very important task, and it is necessary to choose an appropriate method for processing according to specific business needs. The following are some suggestions for desensitizing cached data:

1. Data desensitization requires designing relevant rules based on business needs. Important sensitive information can be protected through enterprise-level encryption algorithms and third-party encryption tools.

2. Scenarios that require desensitization of cached data can be processed in various ways, such as through the cache framework's interceptors, tool classes, etc., to desensitize cached data.

3. While implementing cache data desensitization, the efficiency and performance of the operation need to be considered to avoid negative impacts on system performance.

4. Cache data needs to be detected and cleaned regularly to avoid cache data leakage or improper use.

In short, for cache data desensitization in Java cache technology, business needs and technical implementation need to be comprehensively considered to ensure the security, operability and reliability of data.

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