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A Time Interval based Blockchain Model for Detection of Malicious Nodes in MANET Using Network Block Monitoring Node

机译:基于时间间隔的区块链模型,用于使用网络块监视节点检测MANET中的恶意节点

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Mobile Ad Hoc Networks (MANETs) are infrastructure-less networks that are mainly used for establishing communication during the situation where wired network fails. Security related information collection is a fundamental part of the identification of attacks in Mobile Ad Hoc Networks (MANETs). A node should find accessible routes to remaining nodes for information assortment and gather security related information during route discovery for choosing secured routes. During data communication, malicious nodes enter the network and cause disturbances during data transmission and reduce the performance of the system. In this manuscript, a Time Interval Based Blockchain Model (TIBBM) for security related information assortment that identifies malicious nodes in the MANET is proposed. The proposed model builds the Blockchain information structure which is utilized to distinguish malicious nodes at specified time intervals. To perform a malicious node identification process, a Network Block Monitoring Node (NBMN) is selected after route selection and this node will monitor the blocks created by the nodes in the routing table. At long last, NBMN node understands the location of malicious nodes by utilizing the Blocks created. The proposed model is compared with the traditional malicious node identification model and the results show that the proposed model exhibits better performance in malicious node detection.
机译:移动自组织网络(MANET)是无基础结构的网络,主要用于在有线网络出现故障的情况下建立通信。与安全相关的信息收集是识别移动自组织网络(MANET)中攻击的基本部分。节点应找到到其余节点的可访问路由以进行信息分类,并在路由发现期间收集与安全性有关的信息以选择安全的路由。在数据通信过程中,恶意节点进入网络并在数据传输过程中造成干扰,并降低了系统性能。在此手稿中,提出了一种用于安全相关信息分类的基于时间间隔的区块链模型(TIBBM),用于识别MANET中的恶意节点。所提出的模型构建了区块链信息结构,该结构用于在指定的时间间隔内区分恶意节点。为了执行恶意节点识别过程,在选择路由之后选择一个网络块监视节点(NBMN),该节点将监视由路由表中的节点创建的块。最后,NBMN节点通过利用创建的块了解恶意节点的位置。将该模型与传统的恶意节点识别模型进行比较,结果表明该模型在恶意节点检测中表现出更好的性能。

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