Robust Wireless Localization to Attacks on Access Points

Trustworthy location information is important because it is a critical input to a wide variety of location-based applications. However, the localization infrastructure is vulnerable to physical attacks and consequently the localization results are affected. In this paper, we focus on achieving robust wireless localization when attacks are present on access points. We first investigate the effects of attacks on localization. We then derive an attack-resistant scheme that can be integrated with existing localization algorithms and are not algorithm-specific. Our attack-resistant scheme are based on K-means clustering analysis. We examined our approach using received signal strength (RSS) in widely used lateration-based algorithms. We validated our method in the ORBIT testbed with an IEEE 802.11 (Wi-Fi) network. Our experimental results demonstrate that our proposed approach can achieve comparable localization performance when under access-point attacks as compared to normal situations without attack.