Convergence of Detection Probability, Computational Gains and Asymptotic Analysis of an Algorithm for Physical-Layer Intrusion Detection System

Asymptotic analysis of an algorithm is crucial for practical engineering design. It provides important information about the performance of an algorithm in terms of time complexity, space complexity, and input scale. Based on these performance metrics, engineers can utilize available resources for efficient implementation of the algorithm. In this paper, asymptotic analysis is performed for an algorithm designed for a physical‐layer intrusion detection system (PLIDS). The algorithm first solves Fredholm integral equation of the first kind using Tikhonov regularization. Then, the solution of this equation is used to design a criterion for detection of smart jamming attacks at physical‐layer of the TCP/IP protocol stack. The proposed detection criterion works in constant time. The asymptotic performance metric derived for PLIDS gives insights about its algorithmic behavior. Convergence of detection probability and computational gain of using PLIDS, over higher‐layer intrusion detection systems, are also explained. Finally, apart from asymptotic performance, the detection performance metrics of the PLIDS are also discusse