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Hypergraph clustering model-based association analysis of DDOS attacks in fog computing intrusion detection system

机译:基于超图集群模型的雾气计算入侵检测系统DDOS攻击的关联分析

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The birth of fog computing has given rise to many security threats. Distributed denial of service (DDoS) attacks by intruders on fog nodes will cause system resources to be illegally appropriate. Intrusion detection system (IDS) is a powerful technology that can be used to resist DDoS attacks. In our previous research, we have proposed a fog computing intrusion detection system (FC-IDS) framework. In this paper, we mainly analyze and model the DDoS attacks under the framework of FC-IDS. We propose a hypergraph clustering model based on Apriori algorithm. This model can effectively describe the association between fog nodes which are suffering from the threat of DDoS. Through simulation, we verify that the resource utilization rate of the system can be effectively promoted through the DDoS association analysis.
机译:雾计算的诞生已经引起了许多安全威胁。 通过雾节点的入侵者分发拒绝服务(DDOS)攻击将导致系统资源是非法合适的。 入侵检测系统(IDS)是一种强大的技术,可用于抵抗DDOS攻击。 在我们以前的研究中,我们提出了一种雾计算入侵检测系统(FC-ID)框架。 在本文中,我们主要分析和模拟FC-ID框架下的DDOS攻击。 我们提出了一种基于APRIORI算法的超图聚类模型。 该模型可以有效地描述患有DDOS威胁的雾节点之间的关联。 通过模拟,我们验证了通过DDOS关联分析有效地促进系统的资源利用率。

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