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Secure WiFi Fingerprinting-based Localization

Accurate indoor WiFi localization is attracting more attention nowadays with the wide-spread of location-based services. WiFi fingerprinting is an indoor localization technique, where the location is estimated by mapping the strength of measured WiFi signals from different access points against a previously collected database. WiFi fingerprinting is widely adopted as being natively supported by WiFi mobile devices without any additional costs. A major concern of this technique is that an attacker could easily change the strength of received signals in order to fake the location of the mobile device. Here, we develop novel algorithms to identify attacked access points and make accurate localization in the presence of attacks. We evaluate the performance of our developed algorithms using different WiFi fingerprinting datasets under different attack models. Experimental results show that the proposed algorithms are resistant to attacks and can achieve more robust location estimation than other strategies.