Towards TTP-free lightweight solution for location privacy using location-based anonymity prediction

  • Authors:

  • Sheikh I. Ahamed;Chowdhury S. Hasan;Md. M. Haque;Md. O. Gani

  • Affiliations:

  • Marquette University, Milwaukee, Wisconsin;University of California, Irvine, California;Marquette University, Milwaukee, Wisconsin;Marquette University, Milwaukee, Wisconsin

  • Venue:
  • Proceedings of the 2011 ACM Symposium on Research in Applied Computation
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Location-based services are becoming increasingly popular with the proliferation of location aware devices. It is not possible to access location-based services and preserve privacy at the same time when the user provides exact location information. Cloaking or obfuscating location data is the only way to protect location-privacy. To do that, most of the systems use third party location anonymizer. In this paper, we propose a novel location privacy obfuscation framework without any trusted third party (TTP). Most of the existing solutions attempt to satisfy k-anonymity. In this paper we present the problems of using fixed and user defined k. In order to solve the problems our proposed solution aims to meet probabilistic k-anonymity. Based on historic data expected number of users present in a place is predicted which is used as probabilistic anonymity level. Thus we eliminate the use of any TTP which results into improvement of query-processing time and provides fewer query results for the user to process minimizing the overall response time. Users' exact location information is not revealed in either communication or computation process.