Secure mobile crowdsourcing for WLAN indoor localization

At present, the significantly-developed indoor Location-based services (LBSs) have raised the serious problem of the disclosure of users' location privacy. The existing studies working on indoor localization mainly focus on the localization accuracy and energy efficiency, which normally ignore the security aspect during the localization process. The fingerprint calibration based user-side and trilateration based network-side localization techniques have been widely-used by the state-of-the-art indoor localization systems, whereas neither of them is able to well protect the users' location privacy. In response to this compelling problem, this paper proposes a new secure mobile crowdsourcing approach for WLAN indoor localization. The experimental results demonstrate that the proposed approach is capable of achieving satisfactory localization accuracy as well as avoiding the leakage of users' location privacy in the anonymous WLAN indoor environment.