  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.
