面向认知网络的异常协作节点评估方法研究

发布时间：2019-03-19 10:58

【摘要】：随着无线技术的迅猛发展,用户需求不断增长,无线频谱越发紧张,面临着严重匮乏的问题。认知无线网络的出现为解决频谱资源不足,提高频谱资源利用率,提供了重要思路,已成为近年来广泛研究的热点。它通过动态的感知周围环境信息,并对其进行学习和分析,然后根据当前状况进行相应的规划和决策,从而实现对频谱资源的“二次利用”。然而由于其开放共享的通信资源环境,使其比起传统无线网络,更易受到安全攻击,特别是来自恶意实体和自私实体的干扰及攻击,将破坏感知数据的可信性,威胁可信认知能力,影响认知决策和频谱分配的公平性。传统的网络加解密、身份验证等防御技术,无法有效的解决这些内部安全威胁,而信誉机制作为传统安全方案的补充,能够有效的解决网络内部的安全问题。因此本文借鉴信誉理论,结合认知无线网络自身特征,从整个认知过程出发,针对恶意实体和自私实体,提出一个面向认知网络的异常协作节点评估机制,通过该机制去监督和评估网络中各实体行为,及时发现并处理网络中的恶意和自私实体,从而增强实体合作性,为可靠的频谱接入及网络安全性能提供保障。本文主要工作如下:(1)首先分析当前认知无线网络中存在的安全威胁,梳理了认知无线网络安全机制的研究脉络,分析了在认知无线网络中引入信誉机制的背景和动机。(2)在现有的集中式网络拓扑基础上,针对认知无线网络自身特点,提出基于位置分簇的认知无线网络,考虑到位置因素对认知用户感知特性的影响,弥补了认知网络中拓扑控制方面研究的空白,为信誉评估机制的提出打下模型基础。(3)针对现有方法孤立研究各协议层威胁,缺乏对整个认知过程的考量,以及没有将信誉与认知能力相结合来提高网络安全等缺点。本文在基于位置分簇的网络拓扑基础上,建立了基于认知环的信誉评估机制,通过对节点信誉状态的评估,去发现异常实体,并通过奖惩机制对其进行处理,以提高认知能力的可靠性,保障频谱接入的公平性。(4)通过仿真分析,验证了所提机制对评估和抵御恶意实体及自私实体的有效性及优越性。
[Abstract]:With the rapid development of wireless technology, the demand of users is increasing, and the wireless spectrum is becoming more and more tense, which is facing the problem of serious shortage. The emergence of cognitive wireless network provides an important way to solve the shortage of spectrum resources and improve the efficiency of spectrum resources, and has become a hot topic in recent years. It realizes the "secondary utilization" of spectrum resources by dynamically perceiving the surrounding environment information, learning and analyzing it, and then making corresponding planning and decision-making according to the current situation. However, because of its open and shared communication resource environment, it is more vulnerable to security attacks than traditional wireless networks, especially interference and attacks from malicious entities and selfish entities, which will undermine the credibility of perceptual data. Threat to credible cognitive ability affects the fairness of cognitive decision-making and spectrum allocation. Traditional network encryption and decryption, authentication and other defense techniques can not effectively solve these internal security threats, and reputation mechanism, as the supplement of traditional security schemes, can effectively solve the internal security problems of the network. Therefore, referring to the reputation theory and combining the characteristics of cognitive wireless network, this paper proposes an abnormal cooperative node evaluation mechanism for cognitive networks, aiming at malicious entities and selfish entities, and starting from the whole cognitive process, this paper proposes an abnormal cooperative node evaluation mechanism for cognitive networks. Through this mechanism, we can monitor and evaluate the behavior of entities in the network, detect and deal with the malicious and selfish entities in the network in time, so as to enhance the cooperation of entities and provide the guarantee for reliable spectrum access and network security. The main work of this paper is as follows: (1) at first, the security threats in cognitive wireless network are analyzed, and the research context of cognitive wireless network security mechanism is combed. This paper analyzes the background and motivation of introducing reputation mechanism into cognitive wireless networks. (2) based on the existing centralized network topology, a location-based clustering cognitive wireless network is proposed according to the characteristics of cognitive wireless networks. Considering the influence of location factors on cognitive user perception, it makes up for the gaps in topology control research in cognitive networks, and lays a model foundation for the establishment of reputation assessment mechanism. (3) the threat of each protocol layer is studied in isolation according to the existing methods. Lack of consideration of the whole cognitive process, and lack of credit and cognitive ability to improve network security and other shortcomings. In this paper, based on the network topology based on location clustering, a reputation evaluation mechanism based on cognitive ring is established. By evaluating the reputation status of nodes, abnormal entities are found and processed by reward and punishment mechanism. In order to improve the reliability of cognitive ability and ensure the fairness of spectrum access. (4) the validity and superiority of the proposed mechanism for evaluating and resisting malicious entities and selfish entities are verified by simulation analysis.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN925

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