通过Sybil子图混淆防止对社交图的主动重识别攻击
Preventing active re-identification attacks on social graphs via sybil subgraph obfuscation
摘要：
本文讨论了隐私保护社交图发布背景下的主动重识别攻击。主动攻击是指对手可以利用虚假账户的攻击，也就是sybil节点，以实施可用于在匿名图上重新识别其受害者的结构模式。在本文中，我们提出了一种新的概率解释这种类型的攻击。与以前的隐私属性，其模型的保护，从积极的对手的任务，使受害者节点无法区分的指纹方面的所有潜在的攻击者，我们的新配方引入了一个更完整的视图，其中的攻击是反击联合防止攻击者检索的sybil节点集，并使用这些sybil节点重新识别受害者。根据新的配方，我们表明，隐私属性$k$对称性，在被动攻击的背景下，提供了一个充分条件，防止主动重新识别攻击利用任意数量的sybil节点。此外，我们表明，算法K-匹配，最初设计用于有效地执行相关概念的$k$ -自同构，也保证$k$ -对称性。几个集合的合成图的实证结果证实，我们的方法允许，第一次，发布匿名的社交图（与正式的隐私保证），有效地抵御最强的主动重新识别攻击在文献中报道，即使它利用了大量的sybil节点。
英文摘要：
This paper addresses active re-identification attacks in the context of privacy-preserving social graph publication. Active attacks are those where the adversary can leverage fake accounts, a.k.a. sybil nodes, to enforce structural patterns that can be used to re-identify their victims on anonymised graphs. In this paper we present a new probabilistic interpretation of this type of attacks. Unlike previous privacy properties, which model the protection from active adversaries as the task of making victim nodes indistinguishable in terms of their fingerprints with respect to all potential attackers, our new formulation introduces a more complete view, where the attack is countered by jointly preventing the attacker from retrieving the set of sybil nodes, and from using these sybil nodes for re-identifying the victims. Under the new formulation, we show that the privacy property $k$-symmetry, introduced in the context of passive attacks, provides a sufficient condition for the protection against active re-identification attacks leveraging an arbitrary number of sybil nodes. Moreover, we show that the algorithm K-Match, originally devised for efficiently enforcing the related notion of $k$-automorphism, also guarantees $k$-symmetry. Empirical results on several collections of synthetic graphs corroborate that our approach allows, for the first time, to publish anonymised social graphs (with formal privacy guarantees) that effectively resist the strongest active re-identification attack reported in the literature, even when it leverages a large number of sybil nodes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
