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Collaborative Life-Cycle-Based Botnet Detection in IoT Using Event Entropy

机译:使用事件熵的IOT中基于协作的生命周期的僵尸网络检测

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This paper introduces a collaborative and distributed method for botnet detection in massive networks such as internet of things (IoT) and wide area networks (WAN). The method is model-based and designed as a multi-agent system where the agents are situated on IoT devices. Every agent analyzes the events' entropies, then exchanges its decision with its neighbors aiming at establishing global decision if a botnet is ongoing to be installed within the network or not. Decisions spread over the network where a consensual dominant decision can emerge. In previous similar works, it was necessary to use some central hosts in order to compute global decisions. So, scalability is compromised, and the solution is not suited for massive networks such as IoT. The proposed approach does not require any central control, which allows it to be used in IoT and ad hoc networks. Furthermore, the botnet is detected at the early stage of its life-cycle. Conducted experiments have shown that the proposed approach is well suited for botnet detection in IoT and WAN.
机译:本文介绍了大规模网络中的僵尸网络检测的协作和分布式方法,如事物互联网(IOT)和广域网(WAN)。该方法是基于模型的,设计为一个多智能体系,其中代理位于IOT设备上。每个代理都分析了事件的熵,然后将其与邻居交换其决定,该邻居旨在建立全局决定,如果僵尸网络持续到网络内,则为僵尸网络安装。决策遍布网络,其中可以出现同意的主导决策。在以前的类似作品中,有必要使用一些中央主机来计算全局决策。因此,可伸缩性受到损害,解决方案不适合大规模网络,例如IoT。所提出的方法不需要任何中央控制,这允许它用于IOT和Ad Hoc网络。此外,僵尸网络在其生命周期的早期检测到。进行的实验表明,该方法非常适用于IOT和WAN中的僵尸网络检测。

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