الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Accurate indoor WiFi localization is attracting more attention nowadays with the widespread of location-based services. In- door navigation, child tracking, and location-based advertise- ments are common applications for indoor localization. WiFi fi ting is an indoor localization technique where the lo- cation is estimated by mapping the strength of the measured WiFi signals from diff t Access Points (APs) against a previ- ously collected database. It is widely adopted as being natively supported by the WiFi mobile devices without any additional costs. A major concern of this technique is that an attacker could easily change the strength of the received signals in or- der to fake the location of the mobile device. Here, we develop algorithms to identify the attacked APs and to make accurate localization in the presence of the attack. We evaluate the per- formance of our algorithms using diff t WiFi fi ting datasets under diff rent attack models. Experimental results show that the proposed algorithms are resistant to the applied attack models and can achieve more robust location estimation than other strategies.