位置隐私泄露的一种度量方法

A Novel Measure Method for Location Privacy Leakage

现有的文献大都是对位置隐私保护算法的研究,对于位置隐私保护算法的隐私性度量的研究相对缺乏。为此,针对贪心法的位置K-匿名算法(Greedy-based Location K-anonymous Algorithm,GLKA)提出位置隐私泄露的度量方法。该方法以KL散度(Kullback-Leibler divergence)为基础,将攻击者的背景知识融入其中,用以度量匿名区域中用户位置隐私的泄露。仿真实验表明,该度量方法可以有效地度量攻击者在具有背景知识的情况下,用户位置隐私泄露的水平,从而为位置隐私保护算法的设计与实现提供一定的参考。

Most of the existent literatures are to research on location privacy protection algorithms,but lack the relevant research on privacy metric for location privacy protection algorithms.This paper proposes a measure of location privacy leakage for Greedy-based Location K-anonymous Algorithm(GLKA).The method is based on the Kullback-Leibler divergence and integrates the attacker's background knowledge into measuring the leakage of user's location privacy in the anonymous area.Simulation experiments show that the metric method can effectively measure the level of user's location privacy leakage in the case of attackers with background knowledge,which provides certain reference for the design and implementation of location privacy protection algorithm.