Wireless LAN location-sensing for security applications

This paper considers the problem of using wireless LAN location-sensing for security applications. Recently, Bayesian methods have been successfully used to determine location from wireless LAN signals, but such methods have the drawback that a model must first be built from training data. The introduction of model error can drastically reduce the robustness of the location estimates and such errors can be actively induced by malicious users intent on hiding their location. This paper provides a technique for increasing robustness in the face of model error and experimentally validates this technique by testing against unmodeled hardware, modulation of power levels, and the placement of devices outside the trained workspace. Our results have interesting ramifications for location privacy in wireless networks.

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