Optimized Spoofing and Jamming a Cognitive Radio

Abstract

We examine the performance of a cognitive radio system in a hostile environment where an intelligent adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the adversary may reduce the rate of successful transmission. We present how the adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack.

Strategic Power Allocation With Incomplete Information in the Presence of a Jammer

“…As a matter of fact, the authors adopt an online learning perspective to model the reasoning of the attacker as well as the defender in order to develop an explicit form of optimal power control when the user is aware of the type of learning algorithm used by the jammer and when it has no such information and, thus, also tries to learn the jammer's strategies. In [26], the authors investigate the design of an adversary with optimal power allocation for spoofing and jamming under a Rayleigh fading channel. Assuming that the adversary has full knowledge of the SU system, the authors determine a worst-case optimal energy allocation for spoofing and jamming that the SU adopts using classical optimization techniques.…”

Disruptive Attacks on Video Tactical Cognitive Radio Downlinks

“…This work was extended in [12] to obtain spoofing performance under Nakagami-m fading. In [5] and [13], the optimal power allocation for spoofing and jamming was investigated under an AWGN channel, and Rayleigh fading, respectively. In [5], [13], a generic communication network was studied, and the adversary was optimized to minimize the network throughput.…”

“…In [5] and [13], the optimal power allocation for spoofing and jamming was investigated under an AWGN channel, and Rayleigh fading, respectively. In [5], [13], a generic communication network was studied, and the adversary was optimized to minimize the network throughput. In this paper, we investigate H.264 video communication, and use the received video distortion as the performance metric.…”

“…In this paper, we investigate H.264 video communication, and use the received video distortion as the performance metric. In [5], [13], channel sensing was done only at the cluster head. In this paper, we extend it to distributed sensing.…”

“…In this paper, we extend it to distributed sensing. In [5], [13], users were assigned equal numbers of subcarriers chosen at random. In the current paper we discuss several resource allocation methods and investigate performance for each of those algorithms.…”