Grey Hole Attack Detection and Prevention Methods in Wireless Sensor Networks
Grey Hole Attack Detection and Prevention Methods in Wireless Sensor Networks
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DOI：
10.32604/csse.2022.020993
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发表时间：
2022-01-01
影响因子：
2.2
通讯作者：
Nithyanandam, S.
中科院分区：
文献类型：
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作者：
Chinnaraju, Gowdham;Nithyanandam, S.
无线传感器网络 (WSN) 凭借其灵活性、监控能力和可扩展性等吸引人的特性，在过去十年中获得了广泛关注。它克服了网络管理中遇到的关键问题，并促进了多样化网络架构的发展。动态和自适应路由特性的存在有利于此类网络的快速形成。但灵活的架构也使其极易受到不同类型的攻击，例如拒绝服务 (DoS)。灰洞攻击（GHA）是最关键的攻击类型，因为它对 WSN 组件造成严重影响并最终降低网络性能。在当前的研究中，提出了一种简单的攻击检测、预防和减少方法。这是为了通过警告和阻止恶意暂停以及检查存储表来保护 WSN 免受 GHA 和其他此类攻击。所提出的方法不是阻止整个主机，而是专门消除恶意节点。此外，在没有检测到恶意流量的情况下，主机将被解锁。在当前的研究中，研究人员在 MATLAB 环境下对模型进行了仿真，结果显示性能得到了增强，中央处理器 (CPU) 的利用率和数据包传输率也有所提高。
Wireless Sensor Networks (WSNs) gained wide attention in the past decade, thanks to its attractive features like flexibility, monitoring capability, and scalability. It overcomes the crucial problems experienced in network management and facilitates the development of diverse network architectures. The existence of dynamic and adaptive routing features facilitate the quick formation of such networks. But flexible architecture also makes it highly vulnerable to different sorts of attacks, for instance, Denial of Service (DoS). Grey Hole Attack (GHA) is the most crucial attack types since it creates a heavy impact upon the components of WSN and eventually degrades the performance of network. In current study, a simple attack detection, prevention and reduction approach is proposed. This is to secure the WSN from GHA and other such attacks by warning and blocking the malicious suspensions and by examining the storage table. Instead of blocking the entire host, the presented approach specifically eliminates the malicious nodes. Further, in case of no malicious traffic detection, the host gets unblocked. In current study, the researchers simulated the model under MATLAB environment and the outcomes showed an enhanced performance and increased utilization of Central Processing Unit (CPU) and packet delivery ratio.