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This paper considers spectrum utilization, the probability of detection in cognitive radio (CR) model based on cooperative spectrum sensing with both simultaneous adaptive sensing and transmission at a transmitting secondary user (TSU), and the bit error rate (BER) detection with variation checking at a receiving user (RSU). In this paper, a novel detecting model is proposed in the being considered scenario for the full-duplex TSU's simultaneous sensing and transmitting. A spectrum sensing scheme with an adaptive sensing window is designed to improve the spectrum utilization with a high SNR. At RSU, the BER variation is used further to detect whether a PU is active or not. Data fusion based on the proposed adaptive sensing scheme and the BER detection is processed for better decison on the spectrum holes. Simulation results show that (1) simultaneous spectrum sensing with an adaptive window improves the spectrum utilization compared with a periodical sensing and (2) cooperative spectrum sensing with the BER-assisted detection improves the probability of detection and spectrum utilization compared with the single simultaneous sensing at TSU.

Abstract. This paper presents an effective video steganography method to protect the transmitted biometric data for secure personal identification. Unlike the most of existing biometric data hiding methods, the hiding content in this work is an image set for guaranteeing the valid identification, but not a single image or feature vector. On the basis of human visual system (HVS) model, both interframe and intra-frame motion information are considered to make the hiding method more invisible and robust. Instead of embedding the data redundantly for resisting attacks, the biometric image set is embedded into the video sequence discretely using discrete wavelet transform (DWT). Specially, the sequence number of each frame is embedded into the corresponding frame as a watermark for detecting the integrity of stego-video and guaranteeing the exactly extraction of the biometric image set. Finally, the extracted image set is identified by the biometrics system. Extensive experimental results demonstrate that the proposed method can achieve perfect imperceptibility and good robustness, and guarantee the secure biometrics.

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