User-Defined Privacy Grid System for Continuous Location Based Services

Abstract

In this paper we have demonstrated Location-Based Services (LBSs) which has surfaced as prominent applications in mobile networks. An important challenge in the wide deployment of location-based services (LBSs) is the privacy aware management of location information, providing safeguards for location privacy of mobile clients against vulnerabilities for abuse. This paper describes a scalable architecture for protecting the location privacy from various privacy threats resulting from uncontrolled usage of LBSs. This architecture includes the development of a personalized location anonymization model and a suite of location perturbation algorithms. In particular, our algorithm makes use of a variable-sized cloaking region that increases the location privacy of the user at the cost of additional computation, but maintains the same traffic cost. Our proposal does not require the use of a trusted third-party component, and ensures that we find a good compromise between user privacy and computational efficiency. we propose a user-defined privacy grid system called dynamic grid system (DGS); the first holistic system that fulfils four essential requirements for privacy-preserving snapshot and continuous LBS. Our experiments show that the personalized location k-anonymity model, together with our location perturbation engine, can achieve high resilience to location privacy threats without introducing any significant performance penalty. Experimental results show that our DGS is more efficient than the state-of-the-art privacy preserving technique for continuous LBS.