A Privacy Preserving Method for Crowdsourcing in Indoor Fingerprinting Localization

Abstract

Localization services have gained popularity in recent years to facilitate the daily lives of users. With increasing people desire to use Location Based Services (LBSs), the privacy of users has become critical. Most of these services thus use an anonymizer between Location Service Provider (LSP) and the user to protect the user's identity from LSP. One of the localization techniques in indoor environments is Wi-Fi based location fingerprinting which uses received signal strengths (RSSs) at different locations. In this paper, we propose a method to preserve the privacy of users from anonymizer. Hilbert curve and double encryption technique are used. The simulation results indicate that by using the proposed privacy preserving method, the level of privacy preserving is increased.