一种个性化的k-匿名位置隐私保护算法

Protecting Location Privacy with Personalized k-anonymity

文中提出了一种基于个性k-匿名模型的新的k-匿名算法。在普通匿名算法中增加匿名群记忆模块,从而加快匿名算法的匿名速度。仿真结果表明当用户对安全要求较高的情况下,新匿名算法与普通算法相比具有更快的匿名速度,同时匿名成功率也得到了提升;但在用户对安全要求低的情况下,新算法在匿名速度方面要慢于普通算法,成功率方面的优势也不明显。

This paper presents a new k-anonymity algorithm based on the personalized k-anonymity model. Increasing anonymous group of anonymous memory modules in the ordinary algorithm speeds up the anon- ymous speed. Simulation results show that when the user＇ s requireements for high security situations, the proposed algorithm has faster anonymity speed compared to the ordinary anonymous algorithm, meanwhile the success rate of anonymity has also been improved. When users have the low security requirements, the proposed algorithm has slower anonymous speed than the normal algorithm, advantages of the success rate were not evident.