Multihypothesis Sequential Testing for Illegitimate Access and Collision-Based Attack Detection in Wireless IoT Networks
Bikalpa Upadhyaya, Sumei Sun, Biplab Sikdar · IEEE Internet of Things Journal · 2021
Jamming or illegitimate wireless network access interferes with legitimate communication sessions by mimicking the legitimate transmissions and degrades the network performance. In this article, we propose a methodology to detect such attacks by implementing a multiple hypotheses sequential testing-based detection framework with variance and channel state information (CSI)-based algorithms. The detection framework focuses on distinguishing between legitimate and illegitimate transmissions and the nature of illegitimate transmissions with a quaternary hypotheses test. The quaternary hypotheses include no transmission, legitimate node transmission, illegitimate node transmission, and collision-based attack. We first devise a sequential testing problem on a ternary hypothesis problem and then tackle the remaining hypothesis with both variance-based approach and CSI-based approach. We devise algorithms based on the same and compare their performance. We also compare our approach with the generalized Neyman-Pearson approach based on detection speed. In addition, we present a multiple sensor-based approach to further improve the detection performance through soft- and hard-decision combining. We conduct extensive performance evaluations based on both simulated and measurement data. The numerical results show fewer sample size requirements for the proposed algorithms, leading to faster detection.