Efficiency and detectability of random reactive jamming in carrier sense wireless networks

TL;DR

This paper models the behavior of reactive jammers in wireless networks using Markov chains, analyzing their detectability and optimal strategies, and proposing a detection framework based on carrier sensing violations.

Contribution

It introduces a Markov chain model for reactive jamming detection and optimizes the jammer's behavior to evade detection while disrupting communication.

Findings

Derived the receiver operating characteristic for detection

Identified the tradeoff between jamming effectiveness and detectability

Proposed an optimized reactive jamming strategy

Abstract

A natural basis for the detection of a wireless random reactive jammer (RRJ) is the perceived violation by the detector (typically located at the access point (AP)) of the carrier sensing protocol underpinning many wireless random access protocols (e.g., WiFi). Specifically, when the wireless medium is perceived by a station to be busy, a carrier sensing compliant station will avoid transmission while a RRJ station will often initiate transmission. However, hidden terminals (HTs), i.e., activity detected by the AP but not by the sensing station, complicate the use of carrier sensing as the basis for RRJ detection since they provide plausible deniability to a station suspected of being an RRJ. The RRJ has the dual objectives of avoiding detection and effectively disrupting communication, but there is an inherent performance tradeoff between these two objectives. In this paper we capture the behavior of both the RRJ and the compliant stations via a parsimonious Markov chain model, and pose the detection problem using the framework of Markov chain hypothesis testing. Our analysis yields the receiver operating characteristic of the detector, and the optimized behavior of the RRJ. While there has been extensive work in the literature on jamming detection, our innovation lies in leveraging carrier sensing as a natural and effective basis for detection.