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Practical collusion-resistant conjunctive dynamic searchable encryption with result pattern hiding

delete2026-01-19
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PRE
AI
M
Mingyue Li
H
Honggang Wan
R
Ruizhong Du
G
Guanxiong Ha
X
Xiaoyun Guang
DOI:10.1016/j.jisa.2025.104363delete
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摘要

摘要

En 中文
With the rapid development of cloud computing security, multi-user conjunctive dynamic searchable encryption is receiving more and more attention. However, existing schemes mainly rely on the XSet structure to implement conjunctive queries, which brings significant additional computational costs such as exponentiation, an extra round of communication. In addition, the leakage of keyword pair result pattern (KPRP) has been overlooked. In this work, a practical multi-user conjunction dynamic searchable encryption scheme (named MORF-MUDSE) is proposed, which can against a passive attack by a server colluding with any search user while ensuring the two basic attributes of both forward and backward security. Specifically, a mask-obfuscation random function protocol (named MORF) that includes document keyword set information is designed to implement a new subset validation method of conjunctive queries. This method only completes one round of communication to obtain results, which greatly improves computational efficiency while protecting KPRP. Moreover, a delayed update strategy is proposed, which address the issue of information synchronization between data owner and users during those updates. Through theoretical and experimental analysis, it has been shown that the proposed scheme in this paper has better efficiency in computation and communication compared to the state-of-the-art schemes.

期刊

Journal of Information Security and Applications 封面图
Journal of Information Security and Applications
IF:
3.7
论文数:
2.0K
被引数:
4.9K

机构

H
hebei university
学者数:
1.8K
论文数: 558
被引数: 0
N
nankai university
学者数:
4.8W
论文数: 3.3W
被引数: 74
引用论文

引用论文

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Toward Forward Secure SSE Supporting Conjunctive Keyword Search
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errOAAI
errWang, Yunling; Wang, Jianfeng; Sun, Shifeng; Miao, Meixia; Chen, Xiaofeng
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