Practical searchable encryption scheme against response identity attacks

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Shengming Li , Xuan Jing , Yunling Wang , Xin Xu , Zichen Zhang , Jianfeng Wang
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引用次数: 0

Abstract

Searchable symmetric encryption (SSE) enables efficient keyword-based search over encrypted data while revealing nothing about data and query beyond some pre-defined leakage, such as access pattern and search pattern. A new class of leakage-abuse attacks, called response identity attacks, can exploit access patterns to recover the queried keywords. Although some progress has been made to resist on response identity attacks, it is challenging to design a practical SSE scheme that resists on response identity attacks while protecting the security of data and queries (i.e., end-to-end SSE). To this end, we first present a novel dynamic SSE scheme supporting toward privacy based on the modified Path-ORAM, where the server cannot identify update patterns. We then design a dynamic end-to-end SSE scheme defending response identity attacks under two non-colluding servers model, which splits each encrypted document into the main document and extra blocks, and stores them separately using different obfuscation strategies. The proposed scheme can prevent adversaries from identifying which document in prior knowledge contains the searched keyword while hiding the data content and queries. Experimental results show that our proposed scheme is superior to the state-of-the-art scheme.
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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