一种基于单点收益的轨迹隐私保护方法

A Trajectory Privacy-Preserving Method Based on Single Point Gain

如何在轨迹数据发布时保护用户隐私信息并且最大程度地减少数据损失是隐私保护研究领域的一个重要课题.本文提出一种基于单点收益的轨迹隐私保护方法,在满足用户隐私要求的情况下,根据收益计算结果,在轨迹数据集中抑制位置点或者添加假轨迹,保证每次处理轨迹数据集时能达到最大收益,从而减少信息损失.理论分析和实验结果表明,在隐私容忍度要求较高或者攻击者数量较多的情况下,本文方法能在保证隐私保护强度前提下有效降低数据损失率.

How to preserve users’ privacy information and minimize the loss of information when publishing trajectory data has become an important topic in the research field of privacy preservation.In this paper,we propose a trajectory privacy-preserving method based on single point gain,which satisfies the privacy requirements of users.According to the single point gain values,we suppress location points or add dummy trajectories into the trajectory dataset to ensure that the maximum benefit can be achieved at each iteration,thus reducing the loss of information.Theoretical analysis and experimental results show that,in the case of high privacy tolerance or a large number of attackers,the proposed method effectively reduces the information loss rate while guaranteeing the intensity of privacy preserving.