Identifying Malicious Attacks to Wireless Localization in Bad Channel Conditions

Bad channel conditions can cause serious error in wireless localization. To identify this problem, current methods commonly make use of a consistency analysis. A similar consistency analysis has been adopted in recent studies of location spoofing to identify malicious users. Since they both utilize a consistency analysis, the following problem arise naturally -- how to identify location spoofing in bad channel conditions? In this paper, we present an analysis on the degree of inconsistency. We show that location spoofing will be associated with an inconsistency different from the ones caused by bad channel conditions. Based on this property, we propose an identification method to location spoofing in bad channel conditions. Simulation in wireless sensor networks shows that the proposed method can achieve an average identification rate of 98% with 0% false alarm.