Efficient Detection of Cooperative External Attacks in Wireless Localization Systems

This paper addresses the critical challenge of securing two-way Time-of-Arrival (ToA) localization in Wireless Sensor Networks (WSNs) against cooperative distance-enlargement attacks. Existing schemes often rely on heuristic test statistics, are limited to specific attack strategies e.g., Amplify and Forward (AF), or require collaboration among multiple anchor nodes, which hinders their effectiveness against sophisticated adversaries and often incurs high communication overhead. We propose two novel detection schemes based on signal characteristics that overcome these limitations, offering both high accuracy and low complexity. The first scheme, termed the Efficient Detection Scheme of Distance-Enlargement Attacks using Log-Likelihood Ratio (EDDEA-LLR), leverages the Neyman-Pearson (NP) lemma to derive an optimal test statistic for scenarios involving AF attacks. Recognizing the limitations of existing schemes and the EDDEA-LLR scheme in countering Decode and Forward (DF) attacks, we introduce the Efficient Detection Scheme of Distance-Enlargement Attacks by Embedding a Secret Tag (EDDEA-EST). This scheme exploits embedded secret tags within the challenge signal to effectively detect DF attacks. Importantly, the proposed schemes do not require collaboration among multiple anchor nodes, eliminating the need for additional communication and featuring low computational complexity. We provide a rigorous theoretical analysis, deriving closed-form expressions for the detection performance of both schemes. Through extensive simulations, we demonstrate the superiority of the proposed schemes over existing methods in terms of detection accuracy, robustness against both AF and DF attacks, and comprehensive performance considering communication overhead.