2018Unpublished venueRequires access

OFC: An Approach for Protecting Location Privacy from Location Provider in Location-Based Services

Ming Hou, Hongli Zhang, Yuhang Wang

Open publisher page 1 citations

Abstract

Location-Based Service(LBS) plays an important role in daily life. While LBS provides convenience, it also brings the threat of leaking location privacy. An attacker can even infer users' interests and hobbies based on the location information exposed by them. Although many location privacy protection approaches have been proposed, most of them focus on the stage of providing location to LBS server. In the paper, we propose an Optimal Fingerprints Construction(OFC) algorithm to achieve k-anonymity for users. Different from existing studies, the OFC algorithm focuses on the stage of getting location from Location Provider(LP) and generates dummy user fingerprints to resist adversaries. We first analyze the privacy threats in the positioning process. Considering LP might be potential adversary, we then design the anonymous knowledge base and the location privacy protection algorithm. We evaluate the efficiency of our proposed solution on the smart phone. Simulation results show that our proposed solution is promising.

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What this paper is about

Location-Based Service(LBS) plays an important role in daily life. While LBS provides convenience, it also brings the threat of leaking location privacy. An attacker can even infer users' interests and hobbies based on the location information exposed by them. Although many location privacy protection approaches have been proposed, most of them focus on the stage of providing location to LBS server. In the paper, we propose an Optimal Fingerprints Construction(OFC) algorithm to achieve k-anonymity for users. Different from existing studies, the OFC algorithm focuses on the stage of getting location from Location Provider(LP) and generates dummy user fingerprints to resist adversaries. We first analyze the privacy threats in the positioning process. Considering LP might be potential adversary, we then design the anonymous knowledge base and the location privacy protection algorithm. We evaluate the efficiency of our proposed solution on the smart phone. Simulation results show that our proposed solution is promising.

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Available abstract

Location-Based Service(LBS) plays an important role in daily life. While LBS provides convenience, it also brings the threat of leaking location privacy. An attacker can even infer users' interests and hobbies based on the location information exposed by them. Although many location privacy protection approaches have been proposed, most of them focus on the stage of providing location to LBS server. In the paper, we propose an Optimal Fingerprints Construction(OFC) algorithm to achieve k-anonymity for users. Different from existing studies, the OFC algorithm focuses on the stage of getting location from Location Provider(LP) and generates dummy user fingerprints to resist adversaries. We first analyze the privacy threats in the positioning process. Considering LP might be potential adversary, we then design the anonymous knowledge base and the location privacy protection algorithm. We evaluate the efficiency of our proposed solution on the smart phone. Simulation results show that our proposed solution is promising.

Key concepts: Location-based service, Computer science, Computer security, Anonymity, k-anonymity, Adversary model, Adversary, Service provider

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