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An Effective IDS Against Routing Attacks on Mobile Ad-Hoc Networks

机译:对移动临时网络的路由攻击有效ID

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摘要

The connectivity of mobile networks is increasing heavily and the evolution of the risks is highly dynamic. In Mobile Ad Hoc Network (MANET), attacks and digital attacks are becoming increasingly complex. Due to their nature, these networks make some information unavailable and/or incomplete needed for attacks detection process. Several solutions have been made to ensure the security of mobile networks specially intrusion detection systems (IDS). This solution allows enhancing IDS detection efficiency even with incomplete information about occurred attacks. In this paper, we propose an IDS based on three algorithms NCF, FNF and DPA allowing special traffic abstraction and data collection. We used these algorithms to generate a "behavioral database" for supervised nodes in the network. We study and implement four types of Denial of Service (DoS) attacks, which could disturb the routing process in MANET. These attacks are Blackhole, Grayhole, Wormhole, and Flooding attack. We generate these types of attacks by modifying the normal AODV routing algorithm behavior. We have implemented these attacks using Opnet Modeler 14.5. We proposed a set of IDS nodes to supervise the network behavior using Fuzzy Inference System (FIS). These nodes identify a pattern for each attack behavior to be stored in the "behavioral database". The performance of a network under attack is investigated.
机译:移动网络的连接越来越大,风险的演变是高度动态的。在移动临时网络(MANET)中,攻击和数字攻击变得越来越复杂。由于他们的性质,这些网络使一些信息不可用和/或不完整的攻击检测过程所需的信息。已经进行了几种解决方案以确保移动网络的安全性专门入侵检测系统(ID)。该解决方案允许同时增强IDS检测效率,即使发生了关于发生攻击的不完整信息。在本文中,我们提出了一种基于三种算法NCF,FNF和DPA的ID,允许特殊的流量抽象和数据收集。我们使用这些算法来为网络中的监控节点生成“行为数据库”。我们研究并实施四种类型的拒绝服务(DOS)攻击,这可能会在MANET中扰乱路由过程。这些攻击是黑洞,灰度,虫洞和洪水攻击。通过修改正常的AODV路由算法行为,我们通过修改这些类型的攻击。我们使用OPNet Modeler 14.5实现了这些攻击。我们提出了一组IDS节点来使用模糊推理系统(FIS)监督网络行为。这些节点识别用于存储在“行为数据库”中的每个攻击行为的模式。调查了攻击中网络的性能。

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