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Cognitive radio (CR) technology is designed to improve reliability in communication between users through efficient and dynamic spectrum exploitation. CRs address the problems in spectrum allocation and channel access and improve the rate of radio resource utilization. The flexibility of the CR networks (CRN) and communication medium exposes it to a variety of threats; primary user emulation attack (PUEA) is a malicious and denial-of-service kind of adversary that defaces CRN performance. This manuscript proposes an adaptive learning-based attack detection in CRN for detecting and mitigating PUEA by analyzing the received power of the transmitter. The learning process endorses some beneficial features by distinguishing low spectrum legitimate PU from an adversary. The learning process adopts cyclostationary feature analysis for distinguishing adversaries and low power PU in CR communications. The process of learning is further enhanced by estimating distance variance and communication time-based analysis for improving the rate of signal classification and SU communication rate. The experimental analysis proves the stability of the proposed detection method by improving the SU throughput, with lesser signal classification time and misdetection probability. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the joint resource allocation to provide secure information transmission in a five-node cooperative cognitive radio network, which contains a primary transmitter (PT), a primary receiver (PR), a secondary transmitter (ST), a secondary receiver (SR), and an eavesdropper (E). To ensure the information is securely transmitted, PT and PR use a part of the power to transmit artificial noise (i.e., jamming signal) to confuse the eavesdropper. Specifically, in the first phase, PT transmits its signal, which contains secrecy information and artificial noise, by using all of its power and bandwidth. In the second phase, ST accesses to the PT's licensed bandwidth as a trusted relay by allocating a fraction of the bandwidth and power to forward PT's information with decode-and-forward (DF) relaying protocol. As a reward, ST can utilize the remaining bandwidth and power to transmit its own information simultaneously. We study the joint optimization of the time, bandwidth, and power allocation to maximize ST's transmission rate while satisfying PT's secrecy transmission rate requirements. Numerical results demonstrate that our strategy can achieve a win-win result. [ABSTRACT FROM AUTHOR]

A pattern-based cognitive communication system (PBCCS) that optimizes non-periodic RF waveforms for security applications is proposed. PBCCS is a cross-layer approach that merges the channel encoding and modulation. The transmitter encodes sequences of bits into continuous signal patterns by selecting the proper symbol glossaries. The cognitive receiver preprocesses the received signal by extracting a limited set of wavelet features. The extracted features are fed into an artificial neural network (ANN) to recover the digital data carried by the distorted symbol. The PBCCS system offers a flexible management for robustness against a high noise level and increases the spectral efficiency. In this study, the spectral efficiency and robustness of a PBCCS scheme for an additive white Gaussian noise (AWGN) channel is investigated. The results show that at an SNR of −5 dB, a 3-bit glossary achieves a bit error rate (BER) of 10. Also, the link spectral efficiency (LSE) of the proposed system is 2.61 bps/Hz. [ABSTRACT FROM AUTHOR]

We investigate a method to set the maximum allowable transmit power for a secondary base station in dynamic spectrum sharing among secondary users and primary users. In conventional methods, location information is assumed. Thus, the maximum allowable transmit power can be set by considering the shadowing between the secondary base station and the primary user receivers to satisfy a constraint. Specifically, the probability that the interference from secondary base station exceeds the acceptable level must be less than the constraint target probability. We assume that the location information is not available at the secondary network. Instead, the secondary base station uses the received signal strength from the primary user transmitter for distance estimation. In this case, we have to consider shadowing not only between the secondary base station and the primary user receivers, but also between the primary user transmitter and the secondary receiver(s). We also need to account for the uncertainty of the distance. In order to satisfy the constraint target probability, we proposed a two-step approach to setting the maximum allowable transmit power where a transmission decision margin and a transmit power margin are utilized. To reduce these margins, we also propose cooperative maximum allowable transmit power setting method utilizing also received signal strength values from several secondary users. Simulation results confirm the validity of the analysis and show the effectiveness of the proposed cooperative maximum allowable transmit power setting method, i.e., the capacity based on cooperative maximum allowable transmit power setting method is significantly better than that of non-cooperative maximum allowable transmit power setting method. In addition, we show a proper size of radius of additional separation area to protect primary users by the numerical results. [ABSTRACT FROM AUTHOR]