Personalized location privacy in mobile networks: A social group utility approach

Xiaowen Gong, Xu Chen, Kai Xing, Dong-Hoon Shin, Mengyuan Zhang, Junshan Zhang
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引用次数: 33

Abstract

With increasing popularity of location-based services (LBSs), there have been growing concerns for location privacy. To protect location privacy in a LBS, mobile users in physical proximity can work in concert to collectively change their pseudonyms, in order to hide spatial-temporal correlation in their location traces. In this study, we leverage the social tie structure among mobile users to motivate them to participate in pseudonym change. Drawing on a social group utility maximization (SGUM) framework, we cast users' decision making of whether to change pseudonyms as a socially-aware pseudonym change game (PCG). The PCG further assumes a general anonymity model that allows a user to have its specific anonymity set for personalized location privacy. For the SGUM-based PCG, we show that there exists a socially-aware Nash equilibrium (SNE), and quantify the system efficiency of the SNE with respect to the optimal social welfare. Then we develop a greedy algorithm that myopically determines users' strategies, based on the social group utility derived from only the users whose strategies have already been determined. It turns out that this algorithm can efficiently find a Pareto-optimal SNE with social welfare higher than that for the socially-oblivious PCG, pointing out the impact of exploiting social tie structure. We further show that the Pareto-optimal SNE can be achieved in a distributed manner.
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移动网络中的个性化位置隐私:一种社会群体效用方法
随着基于位置的服务(lbs)的日益普及,人们越来越关注位置隐私。为了保护LBS中的位置隐私,物理上接近的移动用户可以协同工作,集体更改他们的假名,以隐藏他们位置痕迹中的时空相关性。在本研究中,我们利用移动用户之间的社会关系结构来激励他们参与假名更改。利用社会群体效用最大化(social group utility maximization, SGUM)框架,我们将用户是否更改假名的决策视为社会意识假名更改游戏(social -aware pseudonym change game, PCG)。PCG进一步假设了一个通用匿名模型,该模型允许用户为个性化位置隐私设置特定的匿名集。对于基于sgum的PCG,我们证明存在社会意识纳什均衡(SNE),并量化了SNE相对于最优社会福利的系统效率。然后,我们开发了一种贪婪算法,该算法基于仅从策略已确定的用户中获得的社会群体效用来近视地确定用户的策略。结果表明,该算法可以有效地找到社会福利高于社会无关PCG的帕累托最优SNE,指出了利用社会关系结构的影响。我们进一步证明了pareto最优SNE可以在分布式方式下实现。
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