实用的对等连接加密数据库与减少泄漏

IF 8.9 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Qiaoer Xu;Jianfeng Wang;Shi-Feng Sun;Zhipeng Liu;Xiaofeng Chen
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引用次数: 0

摘要

安全连接方案是一类重要的加密数据库查询,已经引起了越来越多的关注。虽然高效查询是最重要的,但数据所有者也强调隐私保护的重要性。最先进的JXT (Jutla和Patranabis ASIACRYPT 2022)通过对称密钥解决方案实现了对加密表的高效连接查询。然而,我们观察到,随着查询数量的增加,JXT无意中泄露了不希望看到的查询结果。在本文中,我们提出了一种新的对等连接方案——一次性连接交叉标记(OTJXT),它可以避免多个查询中额外的结果泄漏,并扩展到与JXT中的自然连接相反的对等连接。具体来说,我们设计了一种使用非线性转换的新数据编码方法,该方法只显示每个查询结果的并集,而不会在JXT中观察到额外的泄漏。此外,OTJXT解决了线性搜索的复杂性问题(Shafieinejad et al.)。ICDE 2022),同时防止多个查询泄漏。最后,我们在TPC-H数据集上实现了OTJXT,并将其性能与JXT和Shafieinejad等人的方案进行了比较。结果表明,OTJXT在搜索和存储效率方面表现优异,实现了$\mathbf {98.5\times}$ (resp)。, $\mathbf {10^{6}\times}$)加速了搜索延迟,并将存储成本降低了62.5%。, 78.5%),而JXT (p。(Shafieinejad等人的方案)。使用OTJXT,在40 MB的数据库上执行TPC-H查询只需要21 ms。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical Equi-Join Over Encrypted Database With Reduced Leakage
Secure join schemes, an important class of queries over encrypted databases, have attracted increasing attention. While efficient querying is paramount, data owners also emphasize the significance of privacy preservation. The state-of-the-art JXT (Jutla and Patranabis ASIACRYPT 2022) enables efficient join queries over encrypted tables with a symmetric-key solution. However, we observe that JXT inadvertently leaks undesirable query results as the number of queries increases. In this paper, we propose a novel equi-join scheme, One-Time Join Cross-Tags (OTJXT), which can avoid additional result leakage in multiple queries and extend to equi-join as opposed to natural join in JXT. Specifically, we design a new data encoding method using nonlinear transformations that reveals only the union of results for each query without extra leakage observed in JXT. Moreover, OTJXT addresses the linear search complexity issue (Shafieinejad et al. ICDE 2022) while preventing multiple query leakage. Finally, we implement OTJXT and compare its performance with JXT and Shafieinejad et al.'s scheme on the TPC-H dataset. The results show that OTJXT outperforms in search and storage efficiency, achieving a $\mathbf {98.5\times }$ (resp., $\mathbf {10^{6}\times }$) speedup in search latency and reducing storage cost by 62.5% (resp., 78.5%), compared to JXT (resp., Shafieinejad et al.'s scheme). Using OTJXT, a TPC-H query on a 40 MB database only takes 21 ms.
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来源期刊
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering 工程技术-工程:电子与电气
CiteScore
11.70
自引率
3.40%
发文量
515
审稿时长
6 months
期刊介绍: The IEEE Transactions on Knowledge and Data Engineering encompasses knowledge and data engineering aspects within computer science, artificial intelligence, electrical engineering, computer engineering, and related fields. It provides an interdisciplinary platform for disseminating new developments in knowledge and data engineering and explores the practicality of these concepts in both hardware and software. Specific areas covered include knowledge-based and expert systems, AI techniques for knowledge and data management, tools, and methodologies, distributed processing, real-time systems, architectures, data management practices, database design, query languages, security, fault tolerance, statistical databases, algorithms, performance evaluation, and applications.
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