Enhanced Privacy-Preserving WiFi Fingerprint Localization from CL Encryption

Abstract

The WiFi fingerprint-based localization method is considered one of the most popular techniques for indoor localization. In INFOCOM'14, Li et al. proposed a wireless fidelity (WiFi) fingerprint localization system based on Paillier encryption, which is claimed to protect both client$C{{}^{\prime}\mathrm{s}}$location privacy and service provider$S{{}^{\prime}\mathrm{s}}$database privacy. However, Yang et al. presented a practical data privacy attack in INFOCOM'18, which allows a polynomial time attacker to obtain$S{{}^{\prime}\mathrm{s}}$database. We propose a novel WiFi fingerprint localization system based on Castagnos-Laguillaumie (CL) encryption, which has a trustless setup and is efficient due to the excellent properties of CL encryption. To prevent Yang et al.'s attack, the system requires that$S$selects only the locations from its database that can receive the nonzero signals from all the available access points in$C{{}^{\prime}\mathrm{s}}$nonzero fingerprint in order to determine$C{{}^{\prime}\mathrm{s}}$location. Security analysis shows that our scheme is secure under Li et al.'s threat model. Furthermore, to enhance the security level of privacy-preserving WiFi fingerprint localization scheme based on CL encryption, we propose a secure and efficient zero-knowledge proof protocol for the discrete logarithm relations in$C{{}^{\prime}\mathrm{s}}$encrypted localization queries.