Multihypothesis Sequential Testing for Illegitimate Access and Collision-Based Attack Detection in Wireless IoT Networks

Abstract

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.