A Multi-factor Trust Management Scheme for Secure Spectrum Sensing in Cognitive Radio Networks
A Multi-factor Trust Management Scheme for Secure Spectrum Sensing in Cognitive Radio Networks
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DOI：
10.1007/s11277-017-4621-5
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发表时间：
2017-11-01
影响因子：
2.2
通讯作者：
Sahoo, Ramesh Kumar
中科院分区：
文献类型：
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作者：
Kar, Sumit;Sethi, Srinivas;Sahoo, Ramesh Kumar
认知无线电（CR）是一种有效利用有限和稀缺的无线电频谱资源的新兴技术。频谱感知是认知无线电系统中的一项关键任务，主要用于检测主用户未使用的无线电频谱或频谱空洞。在这方面，协作频谱感知（CSS）已被证明是一种有效的方式，以提高认知无线电网络（CRN）的频谱空洞检测。然而，这种合作性质使其容易受到许多类型的安全攻击。在本文中，我们专注于这些潜在的CRN特定的安全攻击之一，称为频谱感知数据伪造攻击或拜占庭攻击。其中恶意的网络内部成员报告错误的感知结果，目的是增加感知错误。为了保证CRN的安全性要求，我们提出了一种新的信任管理机制，评估每个节点的可信度参与的CSS计划称为感知信誉（SR）。为了反映复杂性，SR计算涉及多个决策因子，如基于历史的信任因子、活跃因子、激励因子和一致性因子。基于该SR值，可疑用户被识别，恶意用户被过滤出CSS方案的决策过程。我们进一步引入感知信誉链的概念来记录和跟踪识别出的可疑用户的未来行为。理论分析和仿真结果表明，我们提出的恶意用户检测技术具有较高的准确性和较低的误报率的有效性。
Cognitive radio (CR) is an emerging technology for efficient utilization of the limited and scarce radio spectrum resources. Spectrum sensing is a key task in CR system for detecting the unused radio spectrum or spectrum holes by the primary users. In this regard, collaborative spectrum sensing (CSS) has shown to as an efficient way to improve such spectrum holes detection in cognitive radio network (CRN). However, this cooperative nature makes it vulnerable to many types of security attacks. In this paper, we focus one of these potential CRN specific security attack called spectrum sensing data falsification attack or Byzantine attack. In which the malicious internal member of the network, reports false sensing results with a aim to increase the sensing errors. In order to ensure the security requirements of CRN, we proposed a novel trust management mechanism that evaluates the trustworthiness of each node participating in the CSS scheme called sensing reputation (SR). To reflect the complexity, the SR calculation involves multiple decision factors like history based trust factor, active factor, incentive factor and consistency factor. Based on this SR value, the suspicious users are identified and the malicious users are filtered out from the decision making process of the CSS scheme. We further introduce the concept of sensing reputation chain to record and track the future behavior of the identified suspicious users. Theoretical analysis and simulation results demonstrate the effectiveness of our proposed malicious user detection technique with a higher accuracy and lower false alarm rate.