安全多方图计算

Varsha Bhat Kukkala, S. Iyengar, J. Saini
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引用次数: 11

摘要

最近在线网络数据的爆炸式增长和对现实世界网络中普遍拓扑特征的发现,导致了一个新的研究领域的出现,即社会网络。然而,由于敏感网络(包括仇恨网络、信任网络和性关系网络)的数据不可访问,这一领域的许多研究仍未得到探索。本文提出了一种安全的多方协议,该协议允许一组各方在其上计算底层网络。该协议在理论上是信息安全的,并通过k-匿名测试、自环检查和加权边等一系列安全测试进一步提高了协议的安全性。虽然早前已经针对这个问题提出了一些解决方案,但每一个方案的实用性都值得怀疑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure multiparty graph computation
The recent explosion of online networked data and the discovery of universal topological characteristics in real world networks has led to the emergence of a new domain of research, namely, social networks. However, much research in this domain remains unexplored due to the inaccessibility of data of sensitive networks, which include hate networks, trust networks and sexual relationship networks. This paper proposes a secure multiparty protocol which allows a set of parties to compute the underlying network on them. The proposed protocol is information theoretically secure, and its security is further enhanced by a list of security tests, which includes k-anonymity test, check for self loops and weighted edges. Although some solutions have been proposed for this problem earlier, the practicality of each one of those is questionable.
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