Protecting the Moving User’s Locations by Combining Differential Privacy and k -Anonymity under Temporal Correlations in Wireless Networks

Author:

Zhang Weiqi1ORCID,Yin Guisheng1,Sha Yuhai1,Yang Jishen2ORCID

Affiliation:

1. College of Computer Science and Technology, Harbin Engineering University, Heilongjiang, China

2. Department of Computer Science, Georgia State University, Georgia, USA

Abstract

The rapid development of the Global Positioning System (GPS) devices and location-based services (LBSs) facilitates the collection of huge amounts of personal information for the untrusted/unknown LBS providers. This phenomenon raises serious privacy concerns. However, most of the existing solutions aim at locating interference in the static scenes or in a single timestamp without considering the correlation between location transfer and time of moving users. In this way, the solutions are vulnerable to various inference attacks. Traditional privacy protection methods rely on trusted third-party service providers, but in reality, we are not sure whether the third party is trustable. In this paper, we propose a systematic solution to preserve location information. The protection provides a rigorous privacy guarantee without the assumption of the credibility of the third parties. The user’s historical trajectory information is used as the basis of the hidden Markov model prediction, and the user’s possible prospective location is used as the model output result to protect the user’s trajectory privacy. To formalize the privacy-protecting guarantee, we propose a new definition, L&A-location region, based on k -anonymity and differential privacy. Based on the proposed privacy definition, we design a novel mechanism to provide a privacy protection guarantee for the users’ identity trajectory. We simulate the proposed mechanism based on a dataset collected in real practice. The result of the simulation shows that the proposed algorithm can provide privacy protection to a high standard.

Funder

Fundamental Research Funds for the Central Universities

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Reference45 articles.

1. Latency-and-Coverage Aware Data Aggregation Scheduling for Multihop Battery-Free Wireless Networks

2. Location-privacy-aware review publication mechanism for local business service systems;X. Zheng

3. Evaluating the privacy risk of location-based services;J. Freudiger

4. Privacy preserving data quality assessment for high-fidelity data sharing;J. Freudiger

5. Anonymous usage of location-based services through spatial and temporal cloaking;M. Gruteser

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