In a highly evolved big data era, intelligent data analysis can improve social operation efficiency and save resources. However, it also brings masses of conflicts, such as malicious mining and abuse of personal privacy information. This paper introduces a privacy protection scheme for social applications. In this scheme, attribute based searchable encryption is used to defend the security of confidential data and ensure the availability of data. Moreover, the access control structure of ciphertext strategy can meet the needs of data sharing in social applications. Security analysis shows that the scheme does not disclose privacy information in index ciphertext, search trapdoor, and equality test. Compared with plaintext information upload and sharing, the additional performance overhead caused by the scheme is acceptable. The scheme can be actually deployed in social applications.

中文翻译：

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社交应用中的隐私保护：基于关键字搜索的密文策略属性加密

在高度进化的大数据时代，智能数据分析可以提高社会运行效率，节约资源。但同时也带来了恶意挖矿、滥用个人隐私信息等大量矛盾。本文介绍了一种社交应用的隐私保护方案。该方案采用基于属性的可搜索加密来保护机密数据的安全，保证数据的可用性。此外，密文策略的访问控制结构可以满足社交应用中数据共享的需要。安全性分析表明，该方案在索引密文、搜索陷门、相等性测试等方面均未泄露隐私信息。与明文信息上传共享相比，该方案带来的额外性能开销是可以接受的。