Abstract

The wide-ranging application of location-based services (LBSs) through the use of mobile devices and wireless networks has brought about many critical privacy challenges. To preserve the location privacy of users, most existing location privacy-preserving mechanisms (LPPMs) modify their real locations associated with different pseudonyms, which come at a cost either in terms of resource consumption or quality of service, or both. However, we observed that the effect of resource consumption has not been discussed in existing studies. In this paper, we present the user-centric LPPMs against location inference attacks under the consideration of both service quality and energy constraints. Moreover, we modeled the precision-based and dummy-based mechanisms in the context of an existing LPPM framework, and also extended the linear program solutions applicable to them. This study allowed us to specify the LPPMs that decreased the precision of exposed locations or generated dummy locations of the users. Based on this, we evaluated the privacy protection effects of optimal location obfuscation function against an adversary's inference attack function using real mobility datasets. The results indicate that dummy-based mechanisms provide better achievable location privacy under a given combination of service quality and energy constraints, and once a certain level of privacy is reached, both the precision-based and dummy-based mechanisms only perturb the exposed locations. The evaluation results also contribute to a better understanding for the LPPM design strategies and evaluation mechanism as far as the system resource utilization and service quality requirements are concerned.

Highlights

  • Recent advances in mobile computing and wireless communication technologies take advantage of mobile applications to provide location-based services (LBSs) to mobile users

  • The proposed optimization model evaluates the impact of the service quality loss and energy consumption analysis presented in Sections 4.2 and 4.3 on the privacy protection guarantees with different location privacy-preserving mechanisms (LPPMs)

  • The quantitative evaluation model enables us to determine the effectiveness of optimal protection mechanisms against inference attacks in the LBS to ensure the satisfaction of quality of service and resource consumption

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Summary

Introduction

Recent advances in mobile computing and wireless communication technologies take advantage of mobile applications to provide location-based services (LBSs) to mobile users. Many convenient services provided by these LBSs are based on the users’ geographical position to obtain their real-time location data and contextual information about their surroundings. While LBSs bring great benefits to their users, it increases the danger of user privacy breaches due to untrusted third-party adversarial applications. The reason for this is that when users conveniently access various LBSs, they need to report their real-time location information and other related service attributes in the communication network. Due to the existence of untrusted third-party LBS applications, the user private information is bound to cause serious privacy

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