可扩展输出函数的委托多方私有集交集。

IF 2.5 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
PeerJ Computer Science Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI:10.7717/peerj-cs.3141
Aslı Bay
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引用次数: 0

摘要

对来自各方的敏感数据集的操作对于各种实际应用是必不可少的,例如验证购物清单或强制执行禁飞名单。传统的方法通常需要一方访问两个数据集,这带来了隐私问题。私有集合操作提供了一种解决方案,通过启用这些功能而不暴露所涉及的数据。然而,涉及三方或多方的协议通常比不安全的方法慢得多。外包私有集合操作(将计算委托给非串通服务器)可以显著提高性能,尽管目前的协议尚未充分利用这一假设。我们提出了一种新的协议,它消除了对公钥加密的需要。我们的非交互集交集协议仅依赖于可扩展输出函数的安全性,实现了高效率。即使在具有16,384个元素集的10个客户机设置中,交集也可以在54秒内计算出来,而不需要通信开销。我们的结果表明,在不牺牲隐私的情况下,可以取得实质性的性能改进,提出了一种实用而有效的私有集操作方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Delegated multi-party private set intersections from extendable output functions.

Delegated multi-party private set intersections from extendable output functions.

Delegated multi-party private set intersections from extendable output functions.

Delegated multi-party private set intersections from extendable output functions.

Operations on sensitive datasets from different parties are essential for various practical applications, such as verifying shopping lists or enforcing no-fly lists. Traditional methods often require one party to access both datasets, which poses privacy concerns. Private set operations provide a solution by enabling these functions without revealing the data involved. However, protocols involving three or more parties are generally much slower than unsecured methods. Outsourced private set operations, where computations are delegated to a non-colluding server, can significantly improve performance, though current protocols have not fully leveraged this assumption. We propose a new protocol that removes the need for public-key cryptography. Our non-interactive set intersection protocol relies solely on the security of an extendable output function, achieving high efficiency. Even in a ten-client setting with 16,384-element sets, the intersection can be computed in under 54 s without communication overhead. Our results indicate that substantial performance improvements can be made without sacrificing privacy, presenting a practical and efficient approach to private set operations.

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来源期刊
PeerJ Computer Science
PeerJ Computer Science Computer Science-General Computer Science
CiteScore
6.10
自引率
5.30%
发文量
332
审稿时长
10 weeks
期刊介绍: PeerJ Computer Science is the new open access journal covering all subject areas in computer science, with the backing of a prestigious advisory board and more than 300 academic editors.
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