Searchable Encryption Scheme for Personalized Privacy in IoT-Based Big Data

被引:11
|
作者
Li, Shuai [1 ]
Li, Miao [1 ]
Xu, Haitao [1 ]
Zhou, Xianwei [1 ]
机构
[1] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Internet of Things; big data; searchable encryption; personalized privacy needs; index indistinguishability; trapdoor indistinguishability; PUBLIC-KEY ENCRYPTION; KEYWORD GUESSING ATTACKS; SYMMETRIC-ENCRYPTION; EFFICIENT; SECURE; PROTECTION;
D O I
10.3390/s19051059
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The Internet of things (IoT) has become a significant part of our daily life. Composed of millions of intelligent devices, IoT can interconnect people with the physical world. With the development of IoT technology, the amount of data generated by sensors or devices is increasing dramatically. IoT-based big data has become a very active research area. One of the key issues in IoT-based big data is ensuring the utility of data while preserving privacy. In this paper, we deal with the protection of big data privacy in the data storage phase and propose a searchable encryption scheme satisfying personalized privacy needs. Our proposed scheme works for all file types including text, audio, image, video, etc., and meets different privacy needs of different individuals at the expense of high storage cost. We also show that our proposed scheme satisfies index indistinguishability and trapdoor indistinguishability.
引用
收藏
页数:13
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