Privacy-preserving crowdsourced site survey in WiFi fingerprint-based localization

Abstract

Typically, site survey is an inevitable phase for WiFi fingerprint-based localization which is regarded as one of the most promising techniques for indoor localization. However, the site survey can cause potential location privacy leakage for the participants who contribute their WiFi fingerprint measurements. In this paper, we propose a privacy-preserving site survey scheme for WiFi fingerprint-based localization. In the proposed scheme, we use homomorphic encryption to protect the location privacy of the participants which get involved in the site survey. Further, we employ differential privacy model to ensure that the released data will not breach an individual’s location privacy regardless of whether she is present or absent in the site survey group. We theoretically analyze the security of the proposed scheme and use simulation experiments on a real-world data to validate the efficiency of the proposed scheme.