Oct 16, 2015 12:00pm - 2:00pm - Location: EBU1 4309
CWC Advisor: Prof. Pamela Cosman
Video Transmission in Tactical Cognitive Radio Networks Under Disruptive Attacks
We examine the performance of a cognitive radio (CR) system in a hostile environment where an intelligent adversary tries to disrupt communications with a Gaussian noise signal. We analyze a cluster-based network of secondary users (SUs). The adversary can limit access for SUs by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal in the code acquisition interval. By jamming the network during the transmission interval, the adversary can reduce the rate
of successful transmission.
First, we investigate the optimal strategy for spoofing and jamming to minimize the SU throughput in a generic communication system. We study the system performance under attack over slow and fast Rayleigh fading channels. 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. 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. We then extend the analysis to optimal spoofing power allocation for a CR network operating in Nakagami-m fading. The optimized adversary reduces the throughput by a factor of 4 to 5, relative to an adversary who divides power equally across all bands, around 25 dB jamming-to-signal-power ratio (JSR), under slow fading. Under fast fading, the optimized adversary can disrupt the communication at a JSR 10 dB lower than an unoptimized adversary.
We then consider disruptive attacks on a video-transmitting CR network. We investigate the optimal strategy for spoofing, desynchronizing, and jamming a cluster based CR network with a Gaussian noise signal. We use a generalized optimization approach to show how the adversary can optimally allocate its energy across subcarriers during sensing, code acquisition and transmission intervals. We determine a worst-case optimal-energy allocation for spoofing, desynchronizing and jamming, which gives an upper bound to the received video distortion of SUs. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks. The optimized adversary can reduce the received video peak-signal-to-noise-ratio up to 5 dB lower than an equal-power adversary, at low JSR.