Detecting Distance-Spoofing Attacks in Arbitrarily-Deployed Wireless Networks

The present work addresses localization problem in arbitrarily-deployed wireless networks in the presence of malicious attackers that can manipulate (spoof) their distance measurements. This problem is very important for the forthcoming applications that depend on accurate location information, since malicious attacks can potentially lead to disastrous consequences without the consideration of the security aspect. Therefore, this work proposes a new scheme for attacker detection based on generalized likelihood ratio test (GLRT) applied after a preliminary location estimate is obtained based on a simple geometric approach. The detected attacker is then removed from the localization process, which is converted into a generalized trust region sub-problem (GTRS) framework by applying the law of cosines (LC) and solved efficiently via bisectioning. The work also introduces theoretical bounds on the probability of detection in closed-form and studies the performance of the proposed algorithm from computational complexity, success in attacker detection, and localization accuracy perspectives. Our simulations corroborate the effectiveness of the proposed scheme, offering good localization accuracy and detection performance even in noisy environments