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k-Trustee: Location injection attack-resilient anonymization for location privacy

机译:k-Trustee:用于位置隐私的位置注入攻击-弹性匿名

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Cloaking-based location privacy preserving mechanisms have been widely proposed to protect users' location privacy when using location-based services. A fundamental limitation of such mechanisms is that users and their location information in the system are inherently trusted by the Anonymization Server without any verification. In this paper, we show that such an issue could lead to a new class of attacks called location injection attacks which can successfully violate users' in-distinguishability among a set of users. We propose and characterize location injection attacks by presenting a set of attack models and quantifying the costs associated with them. We present and evaluate k-Trustee, a trust-aware location cloaking mechanism that is resilient to location injection attacks and guarantees a lower bound on the user's in-distinguishability. k-Trustee guarantees that each user in a given cloaked region can achieve the required k-Anonymity by including at least k-1 other trusted users in the cloaked region. We demonstrate the effectiveness of k-Trustee through extensive experiments in a real-world geographic map and our experimental results show that the proposed cloaking algorithm guaranteeing k-Trustee is effective against various location injection attacks. (C) 2018 Elsevier Ltd. All rights reserved.
机译:已经广泛提出了基于隐身的位置隐私保护机制,以在使用基于位置的服务时保护用户的位置隐私。这种机制的基本局限性在于,匿名性服务器固有地信任用户及其在系统中的位置信息,而无需任何验证。在本文中,我们证明了这种问题可能导致一类称为位置注入攻击的新型攻击,该攻击可以成功违反一组用户之间的用户不可区分性。通过提出一组攻击模型并量化与之相关的成本,我们提出并表征了位置注入攻击。我们介绍并评估k-Trustee,这是一种信任感知的位置隐藏机制,可抵抗位置注入攻击,并保证用户的不可区分性下限。 k-Trustee保证给定隐蔽区域中的每个用户都可以通过在隐蔽区域中包含至少k-1个其他受信任用户来实现所需的k-匿名性。我们通过在真实世界的地理环境中进行广泛的实验来证明k-Trustee的有效性,我们的实验结果表明,所提出的掩盖算法可确保k-Trustee对各种位置注入攻击均有效。 (C)2018 Elsevier Ltd.保留所有权利。

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