Abstract

Recent years have witnessed the rapid growth of location-based services (LBSs) for mobile social network applications. To enable location-based services, mobile users are required to report their location information to the LBS servers and receive answers of location-based queries. Location privacy leak happens when such servers are compromised, which has been a primary concern for information security. To address this issue, we propose the Location Privacy Preservation Scheme (LPPS) based on distributed cache pushing. Unlike existing solutions, LPPS deploys distributed cache proxies to cover users mostly visited locations and proactively push cache content to mobile users, which can reduce the risk of leaking users’ location information. The proposed LPPS includes three major process. First, we propose an algorithm to find the optimal deployment of proxies to cover popular locations. Second, we present cache strategies for location-based queries based on the Markov chain model and propose update and replacement strategies for cache content maintenance. Third, we introduce a privacy protection scheme which is proved to achievek-anonymity guarantee for location-based services. Extensive experiments illustrate that the proposed LPPS achieves decent service coverage ratio and cache hit ratio with lower communication overhead compared to existing solutions.

Highlights

  • Mobile social network applications are booming in recent years

  • We proved that the proposed privacy preservation scheme based on cache pushing can achieve k-anonymity assurance, which is resilient to the compromise of location-based services (LBSs) server or proxies

  • We pick the most probable locations to push to the mobile users passing, which can reduce the risk of location report and the communication overhead to the LBS server

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Summary

Introduction

Mobile social network applications are booming in recent years. With the rapid development of localization technologies (such as GPS) and Mobile Internet, mobile social network applications with location-based service (LBS) embedded are very popular such as Foursquare and Twitter. As each coin has two sides, the LBS for mobile social applications may leak the users’ location trajectory and so on, with a rising concern in location-based service about privacy protection. A user can achieve k-anonymity by sending out k queries with different locations to the server and choosing the desired answer from the responses. Such method wastes network bandwidth and causes extra overhead in both client and server sides. A few works introduced trust-worthy middleware or cache proxies by using random noise to conceal

A LBS server
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