Verifiable Searchable Encryption Framework Against Insider Keyword-Guessing Attack in Cloud Storage

被引:72
作者
Miao, Yinbin [1 ,2 ]
Tong, Qiuyun [1 ,2 ]
Deng, Robert H. [3 ,4 ]
Choo, Kim-Kwang Raymond [5 ]
Liu, Ximeng [6 ]
Li, Hongwei [7 ]
机构
[1] Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
[2] State Key Lab Cryptol, POB 5159, Beijing 100878, Peoples R China
[3] Singapore Management Univ, Dept Informat Syst, Singapore 178902, Singapore
[4] Singapore Management Univ, Dept Elect & Comp Engn, Singapore 178902, Singapore
[5] Univ Texas San Antonio, Dept Informat Syst & Cyber Secur, San Antonio, TX 78249 USA
[6] Fuzhou Univ, Coll Math & Comp Sci, Key Lab Informat Secur Network Syst, Fuzhou 350108, Peoples R China
[7] Univ Elect Sci & Technol China, Dept Comp Sci & Engn, Chengdu 610051, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Searchable encryption; insider keyword-guessing attack; multi-keyword search; multi-key encryption; dynamic update; PUBLIC-KEY ENCRYPTION; INDUSTRIAL INTERNET; SECURE; REVOCATION;
D O I
10.1109/TCC.2020.2989296
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Searchable encryption (SE) allows cloud tenants to retrieve encrypted data while preserving data confidentiality securely. Many SE solutions have been designed to improve efficiency and security, but most of them are still susceptible to insider Keyword-Guessing Attacks (KGA), which implies that the internal attackers can guess the candidate keywords successfully in an off-line manner. Also in existing SE solutions, a semi-honest-but-curious cloud server may deliver incorrect search results by performing only a fraction of retrieval operations honestly (e.g., to save storage space). To address these two challenging issues, we first construct the basic Verifiable SE Framework (VSEF), which can withstand the inside KGA and achieve verifiable searchability. Based on the basic VSEF, we then present the enhanced VSEF to support multi-keyword search, multi-key encryption and dynamic updates (e.g., data modification, data insertion, and data deletion) at the same time, which highlights the importance of practicability and scalability of SE in real-world application scenarios. We conduct extensive experiments using the Enron email dataset to demonstrate that the enhanced VSEF achieves high efficiency while resisting to the inside KGA and supporting the verifiability of search results.
引用
收藏
页码:835 / 848
页数:14
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