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Projection Pursuit Based Wormhole Detection in Ad Hoc Network

机译:基于投影追求临时网络的蠕虫孔检测

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Ad hoc networks have found increasingly wide applications in many fields nowadays. At the meantime, various attacks against Ad hoc have emerged, such as wormhole attack, denial of service (DoS), black holes attack and gray holes attack, among which wormhole attack is most difficult to detect and is most destructive to the network. At present, there are limitations in various worm hole detection mechanisms, some require that the data collected should conform to specific probability distribution, and some even require the introduction of encryption and authentication mechanism or additional equipment and are poor in flexibility. Projection pursuit (PP) based wormhole detection mechanism does not depend on specific data distribution and can directly mine data dependency for wormhole evaluation on network nodes. PP adopts genetic algorithm to optimize projection direction and the projection results obtained can directly be used in wormhole evaluation. In this paper, we first simulate AODV routing protocol based Ad hoc network by using NS2.After data collection and through comparing a one dimensional projection and two dimensional projections, we find that one-dimensional project has little data loss and high accuracy in wormhole detection. Projection pursuit based wormhole detection gives us new insights into wormhole detection and is a wormhole detection completely based on statistics.
机译:现在,Ad Hoc网络在许多领域发现了越来越广的应用。与此同时,已经出现了针对特设的各种攻击,例如虫洞攻击,拒绝服务(DOS),黑洞攻击和灰色孔攻击,其中虫洞攻击最难以检测,并且对网络最具破坏性。目前,各种蠕虫孔检测机制存在局限性,有些要求收集的数据应符合特定的概率分布,并且有些需要引入加密和认证机制或附加设备,并且灵活性差。投影追踪(PP)基于蠕虫孔检测机制不依赖于特定的数据分布,并且可以直接对网络节点进行蠕虫孔评估的挖掘数据依赖性。 PP采用遗传算法来优化投影方向,并且可以直接用于蠕虫孔评估的投影结果。在本文中,我们首先通过使用NS2来模拟基于AODV路由协议的ad hoc网络。通过比较一维投影和二维预测,我们发现一维项目在蠕虫检测中具有很小的数据丢失和高精度。投影追踪基于蠕虫孔检测使我们对蠕虫孔检测的新见解,并且是基于统计数据的蠕虫检测。

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