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

机译:最优阈值选择方法在认知无线网络中增强主要用户仿真攻击下的吞吐量性能

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摘要

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应对频谱稀缺。由于认知无线电网络(CRN)架构的独特特性,它允许各种未知的无线设备机会性地访问主要用户(PU)的频带,这对网络构成了安全威胁。常见威胁之一是主要用户仿真(PUE)攻击,其中一些恶意用户试图模仿主要信号并欺骗次要用户(SU),以阻止他们访问空闲的PU频谱频段。在本文中,通过建议的最佳阈值选择方法在PUE攻击下提高了SU的吞吐量性能,该方法将SU频谱访问是混合的(即覆盖或底层)的总错误概率降至最低。提出了一种评估框架,用于评估拟议防御方案下的SU吞吐量。指出了提出的方案后,诸如感知时间,攻击者的力量和攻击者的存在概率等几个参数对SU的吞吐性能的影响,并与常规方案进行了比较。基于最佳阈值选择的拟议方案优于基于固定阈值的常规方案。还指出了攻击者对SU的虚警概率和总错误概率的影响。在MATLAB中开发了一个模拟测试台,以验证我们的分析结果。

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