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Enhanced Throughput Performance under Primary User Emulation Attack in Cognitive Radio Networks by Optimal Threshold Selection Approach

机译:通过最优阈值选择方法在认知无线网络中提高主用户仿真攻击下的吞吐量性能

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Cognitive radio (CR) provides dynamic spectrum access to combat spectrum scarcity. Due to the unique characteristic of cognitive radio network (CRN) architecture, it allows various unknown wireless devices to opportunistically access the primary user's (PU) spectrum bands which imposes security threats to the network. One of the common threats is a primary user emulation (PUE) attack, where some malicious users try to mimic the primary signal and deceive secondary users (SUs) to prevent them from accessing the vacant PU spectrum bands. In this paper, the throughput performance of a SU has been enhanced under PUE attack by a proposed optimal threshold selection approach that minimizes the total error probability where SU spectrum access is hybrid, i.e., either in overlay or in underlay. An analytical framework for evaluating the throughput of a SU under proposed defense scheme is presented. Impacts of several parameters such as sensing time, attacker's strength and attacker's presence probability on the throughput performance of a SU following the proposed scheme are indicated and compared with conventional scheme. The proposed scheme based on optimal threshold selection outperforms the conventional scheme based on a fixed threshold. The effects of attackers on false alarm probability and total error probability of SU are also indicated. A simulated test bed is developed in MATLAB to validate our analytical results.
机译:认知无线电(CR)提供动态频谱访问,以对抗频谱稀缺性。由于认知无线电网络(CRN)架构的独特特征,它允许各种未知的无线设备机会地访问主要用户(PU)频谱频带,这对网络施加了安全威胁。其中一个常见的威胁是主要用户仿真(PUE)攻击,其中一些恶意用户试图模仿主要信号和欺骗二级用户(SUS)以防止它们访问空置PU频谱频带。在本文中,通过提出的最佳阈值选择方法在Pue攻击下提高了SU的吞吐量性能,这提出了最大限度的阈值选择方法,其最小化SU频谱接入是混合的总误差概率,即覆盖物或底层。提出了一种评估拟议防御方案吞吐量的分析框架。的几个参数,如感测时间的影响,攻击者的力量和所提出的方案以下对SU的吞吐量性能攻击者的存在概率指示,并与传统方案相比。基于最优阈值选择的提出方案优于基于固定阈值的传统方案。还指出了攻击者对误报概率和SU总误差概率的影响。 MATLAB开发了模拟试验床,以验证我们的分析结果。

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