A Privacy-Preserving Fuzzy Localization Scheme with CSI Fingerprint

CSI fingerprint localization is an advanced and promising technique for indoor localization, which identifies the user´s location by mapping his measured CSI against the server´s CSI fingerprint database. This approach is highlighted due to its high granularity for location distinction and strong robustness to noise disturbances, but it also causes potential privacy leakage for the three participants in localization process: the user, the server, and the AP. Currently, there has been little research done on this issue, and the existing work often ignores the privacy concern on the AP. To fill the gap, this paper develops a privacypreserving fuzzy localization scheme with CSI fingerprint. On one hand, it leverages the property of CSI training to guarantee the randomness and independence of the user´s measurement in each time of localization, and uses homomorphic encryption to achieve the data transmission and measurement comparison in cipher. These operations enable our scheme to preserve the location privacy of the user and APs as well as the data privacy of the server. On the other hand, the adoption of CSI fingerprint and fuzzy logic enhances the localization accuracy greatly. Through simulation experiments performed on CRAWDAD database, the efficiency of our proposed scheme is validated.