In this paper, we propose a technique to ensure security in cooperative spectrum sensing for video streaming application in cognitive radio network. Sensing based clustering algorithm puts together the cognitive radios into clusters to mitigate cooperative overhead and to reduce energy consumption. In order to avert primary user emulation attacks, we introduce authentication signature ID algorithm which provides authority for the licensed user to use the spectrum. To diminish spectrum sensing data falsification attacks, we exploit hamming algorithm to expel forgery node from spectrum sensing decision. Furthermore, the primary radio network channel allocation algorithm is employed to precisely deliver the video with high quality and lower delay. For video transmission in a cognitive radio network, we compress the video frames using block truncation coding-pattern fitting in order to reduce bandwidth requirement. This compression technique offers good video transmission with a high compression ratio in a cognitive radio network, due to trade-off among quality, bit rate and decoding time. Simulation results reveal that there is a significant improvement in the detection rate of idle channel and reduction of delay for high-quality video transmission.
['D. Lakshmi Chaitanya', 'K. Manjunatha Chari']
Secure Channel Allocation Approach for Video Streaming in Cognitive Radio Networks