Understanding Social Networks Properties for Trustworthy Computing

Aziz Mohaisen, Huy Tran, Nicholas Hopper, Yongdae Kim
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引用次数: 10

Abstract

The ever-increasing popularity of social networks opens new directions for leveraging social networks to build primitives for security and communication, in many contexts. Such primitives utilize the trust in these social networks to ensure collaboration and algorithmic properties exhibited in such networks to argue for the effectiveness of such primitives. Despite the importance of such properties and their quality to the operation of these primitives, less effort is made to measure these properties and understand the relationship among them and to other characteristics of social networks. We extend our earlier results measuring the mixing time, to investigate a new property used for building Sybil defenses, namely the expansion of social graphs. We measure the expansion of social graphs, and show quantitatively that, with a few exceptions, it is sufficient to support Sybil defense mechanisms based on expansion. We relate the mixing time of social graphs to graph degeneracy, which captures cohesiveness of the graph. We experimentally show that fast-mixing graphs tend to have a larger single core whereas slow mixing graphs tend to have smaller multiple cores. While this study provides quantitative evidence relating the mixing time to coreness of the graph, it also agrees with our previous observations about the tight-knit community structure in slow mixing social graphs.
了解可信赖计算的社会网络属性
社交网络的日益普及为利用社交网络在许多环境中构建安全性和通信的原语开辟了新的方向。这些原语利用这些社会网络中的信任来确保协作,并在这些网络中展示算法属性来证明这些原语的有效性。尽管这些属性及其质量对这些原语的操作很重要,但很少有人去衡量这些属性并理解它们之间的关系以及它们与社会网络的其他特征之间的关系。我们扩展了之前测量混合时间的结果,以研究用于构建Sybil防御的新属性,即社交图的扩展。我们测量了社交图谱的扩展,并定量地表明,除了少数例外,它足以支持基于扩展的Sybil防御机制。我们将社交图的混合时间与图的退化联系起来,图的退化反映了图的内聚性。我们通过实验表明,快速混合图往往具有较大的单核,而缓慢混合图往往具有较小的多核。虽然这项研究提供了有关混合时间与图的核心度的定量证据,但它也与我们之前关于缓慢混合社交图中紧密结合的社区结构的观察结果一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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