2,714 research outputs found

    A Study on Techniques/Algorithms used for Detection and Prevention of Security Attacks in Cognitive Radio Networks

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    In this paper a detailed survey is carried out on the taxonomy of Security Issues, Advances on Security Threats and Countermeasures ,A Cross-Layer Attack, Security Status and Challenges for Cognitive Radio Networks, also a detailed survey on several Algorithms/Techniques used to detect and prevent SSDF(Spectrum Sensing Data Falsification) attack a type of DOS (Denial of Service) attack and several other  Network layer attacks in Cognitive Radio Network or Cognitive Radio Wireless Sensor Node Networks(WSNN’s) to analyze the advantages and disadvantages of those existing algorithms/techniques

    Machine Learning Approaches for Spectrum Management in Cognitive Radio Networks

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    Cognitive radio (CR) provides a better way for utilization of spectrum resource by introducing an opportunistic usage of the frequency bands that are not heavily occupied by a licensed spectrum user or a primary user (PU). In cognitive radio, the detection and estimation of PU channel availability (unoccupied spectrum) are the key challenges that need to be overcome in order to prevent the interference with licensed spectrum user and improve spectrum resource utilization efficiency. This chapter focuses on developing new ways for detecting and estimating primary user channel availability based on machine-learning (ML) techniques

    Novel evaluation framework for sensing spread spectrum in cognitive radio

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    The cognitive radio network is designed to cater to the optimization demands of restricted spectrum availability. A review of existing literature on spectrum sensing shows that there is still a broader scope for its improvement. Therefore, this paper introduces an efficient computational framework capable of evaluating the effectiveness of the spread spectrum concept in the context of cognitive radio network in a more scalable and granular way. The proposed method introduces a dual hypothesis using a different set of dependable parameters to emphasize the detection of optimal energy for a low signal quality state over the noise. The proposed evaluation framework is benchmarked using a statistical analysis method not present in any existing approaches toward spread spectrum sensing. The simulated outcome of the study exhibits that the proposed system offers a significantly better probability of detection than the current system using a simplified evaluation scheme with multiple test parameters
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