检测和预防黑洞攻击的模糊启发式方法

Elamparithi Pandian, Ruba Soundar, Shenbagalakshmi Gunasekaran, Shenbagarajan Anantharajan
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引用次数: 0

摘要

移动特设局域网(MANET)是一组没有固定基础设施支持的计算节点。网络中的每个节点都通过无线链路相互通信。然而,在城域网中,节点的动态拓扑结构是保证网络安全、识别和防止黑洞攻击的关键所在。本文根据节点认证、信任值、证书颁发机构(CA)、能量水平和信息完整性,设计了一种新型模糊推理系统,用于黑洞攻击检测。在城域网中启动路由发现过程之前,所提出的工作主要集中在节点认证上。仿真使用网络仿真器(NS2)进行,其中设计的模糊推理系统只向受信任的节点提供证书,从而显示出更好的性能。这有助于检测恶意节点并防止黑洞攻击。数据包传输率(PDR)的提高增强了吞吐量,端到端延迟也因更好的性能结果而减少。这证明该系统更加可靠,可用于军事应用中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy Heuristics for Detecting and Preventing Black Hole Attack
Mobile Ad-hoc Networks (MANET) is a set of computing nodes with there is no fixed infrastructure support. Every node in the network communicates with one another through wireless links. However, in MANET, the dynamic topology of the nodes is the vital demanding duty to produce security to the network and the black hole attacks get identified and prevented. In this paper, a novel fuzzy inference system is designed for black hole attack detection depending on the node authentication, trust value, Certificate Authority (CA), energy level, and message integrity. Before initiating the route discovery process in MANET, the proposed work mainly concentrates on node authentication. The simulation gets carried out using the Network Simulator (NS2), wherein the fuzzy inference system designed shows better performance by providing a certificate to only the trusted nodes. This helps the malicious nodes detection and prevents the black hole attack. The improvement in Packet Delivery Ratio (PDR) enhances throughput and the end to end delay gets reduced through better performance results. This proves that the system is more reliable and recovered to be used in military applications
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