Abstract

With the increasing convenience of location-based services (LBSs), there have been growing concerns about the risk of privacy leakage. We show that existing techniques fail to defend against a statistical attack meant to infer the user’s location privacy and query privacy, which is due to continuous queries that the same user sends in the same location in a short time, causing the user’s real location to appear consecutively more than once and the query content to be the same or similar in the neighboring query. They also fail to consider the hierarchical structure of the address, so locations in an anonymous group may be located in the same organization, resulting in leaking of the user’s organization information and reducing the privacy protection effect. This paper presents a dummy generation scheme, considering the hierarchical structure of the address (DGS-HSA). In our scheme, we introduce a novel meshing method, which divides the historical location dataset according to the administrative region division. We also choose dummies from the historical location dataset with the two-level grid structure to realize the protection of the user’s location, organization information, and query privacy. Moreover, we prove the feasibility of the presented scheme by solving the multi-objective optimization problem and give the user’s privacy protection parameters recommendation settings, which balance the privacy protection level and system overhead. Finally, we evaluate the effectiveness and the correctness of the DGS-HSA through theoretical analysis and extensive simulations.

Highlights

  • With the rapid development of smart terminal technology, positioning technology, and mobileInternet technology, location-based service (LBS) is increasingly penetrating all aspects of life, such as inquiring about nearby restaurants, hotels, and so on, bringing great convenience to people

  • We point out two problems of the existing location privacy protection schemes

  • The continuous query request scenario for the same user in the same location and the hierarchical structure of the address corresponding to the location are not considered, which makes it difficult for the privacy protection scheme to resist statistical attacks and hard to achieve the ideal privacy protection effect

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Summary

Introduction

With the rapid development of smart terminal technology, positioning technology, and mobile. Location-based service (LBS) is increasingly penetrating all aspects of life, such as inquiring about nearby restaurants, hotels, and so on, bringing great convenience to people. People enjoy location-based services over the cyber. Considering the network security situation, people inevitably suffer serious cyber risks, e.g., malware [1], spyware [2], encryption for malicious. Sci. 2020, 10, 548 purposes [3], and zero-day attacks [4]. As one of the cyber risks, is drawing more and more attention

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