Big Data Research ›› 2023, Vol. 9 ›› Issue (1): 141-152.doi: 10.11959/j.issn.2096-0271.2022042

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Trajectory differential privacy protection method based on exponential mechanism

Huicong JIAO, Wenju LIU, Ze WANG   

  1. College of Computer Science and Technology, Tiangong University, Tianjin 300384, China
  • Online:2023-01-15 Published:2023-01-01

Abstract:

A trajectory differential privacy protection method based on exponential mechanism was proposed, aiming at the problem of privacy disclosure caused by ignoring semantic information carried by location points in traditional trajectory data protection.For the privacy disclosure caused by the dual attribute information of geographic features and semantic features of location, an available scoring function for location points was designed according to the characteristics of the index mechanism in differential privacy.And the function randomized the output to protect the trajectory effectively privacy.This scheme could reduce the size of data sets while ensure location privacy, prevent semantic background inference attacks and improve data availability.Experiments were carried out on real trajectory data sets, and the experimental results showed that the proposed method not only effectively protected the privacy of the user's stay area location, but also effectively improved the data availability while ensured the privacy intensity.

Key words: differential privacy, space-time trajectory, semantic location, index mechanism

CLC Number: 

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