An Improved Security Mechanism in Cognitive Radio Networks

Huayi Wu, Baohua Bai
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引用次数: 13

Abstract

As one type of the attacks happening in MAC layer of distributed cognitive radio networks, a selfish behavior can degrade network performance significantly. In this paper, we analyze the characteristics of selfish behavior and the methods how to expose it. In order to improve the self-giving cooperation between the nodes in cognitive radio networks and increase the fairness index of the whole networks, a rigorous punishment mechanism based on a puzzle model was proposed in this paper. The punishment mechanism was used both in a common control channel and a data channel. The results of stimulations show that the proposed punishment mechanism increases the fairness index of the cognitive radio networks and improves the self-giving cooperation between nodes in the networks.
一种改进的认知无线网络安全机制
作为一种发生在分布式认知无线网络MAC层的攻击,自私行为会显著降低网络性能。本文分析了私心行为的特点及揭露私心行为的方法。为了提高认知无线网络中节点间的自我给予性合作,提高整个网络的公平性指数,提出了一种基于谜题模型的严格惩罚机制。惩罚机制在公共控制通道和数据通道中都得到了应用。仿真结果表明,所提出的惩罚机制提高了认知无线网络的公平性指数,提高了网络节点间的自我给予合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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