CLM：面向轨迹发布的差分隐私保护方法

doi:10.11959/j.issn.1000-436x.2017119

Abstract

Abstract:

In order to solve the problem existing in differential privacy preserving publishing methods that the independent noise was easy to be filtered out,a differential privacy publishing method for trajectory data (CLM),was proposed.A correlated Laplace mechanism was presented by CLM,which let Gauss noises pass through a specific filter to produce noise whose auto-correlation function was similar with original trajectory series.Then the correlated noise was added to the original track and the perturbed track was released.The experimental results show that the proposed method can achieve higher privacy protection and guarantee better data utility compared with existing differential privacy preserving publishing methods for trajectory data.

Key words: trajectory publishing, privacy preserving, differential privacy, correlated Laplace

CLC Number:

TP309.2

Hao WANG,Zheng-quan XU,Li-zhi XIONG,Tao WANG. CLM:differential privacy protection method for trajectory publishing[J]. Journal on Communications, 2017, 38(6): 85-96.

Figures/Tables 8

References 33

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