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A trust-based game theoretical model for cooperative intrusion detection in multi-cloud environments

机译:多云环境下基于信任的博弈理论用于协同入侵检测

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摘要

Cloud systems are becoming more complex and vulnerable to attacks. Cyber attacks are also becoming more sophisticated and harder to detect. Therefore, it is increasingly difficult for a single cloud-based intrusion detection system (IDS) to detect all attacks, because of limited and incomplete knowledge about attacks. The recent researches in cyber-security have shown that a co-operation among IDSs can bring higher detection accuracy in such complex computer systems. Through collaboration, a cloud-based IDS can consult other IDSs about suspicious intrusions and increase the decision accuracy. The problem of existing cooperative IDS approaches is that they overlook having untrusted (malicious or not) IDSs that may negatively effect the decision about suspicious intrusions in the cloud. Moreover, they rely on a centralized architecture in which a central agent regulates the cooperation, which contradicts the distributed nature of the cloud. In this paper, we propose a framework that enables IDSs to distributively form trustworthy IDSs communities. We devise a novel decentralized algorithm, based on coalitional game theory, that allows a set of cloud-based IDSs to cooperatively set up their coalition in such a way to make their individual detection accuracy increase, even in the presence of untrusted IDSs.
机译:云系统变得越来越复杂,容易受到攻击。网络攻击也变得越来越复杂,更难以检测。因此,由于有关攻击的知识有限且不完整,因此单个基于云的入侵检测系统(IDS)很难检测到所有攻击。网络安全方面的最新研究表明,IDS之间的合作可以在如此复杂的计算机系统中带来更高的检测精度。通过协作,基于云的IDS可以咨询其他IDS有关可疑入侵的信息,并提高决策准确性。现有协作式IDS方法的问题在于,它们忽略了具有不可信(无论是否恶意)的IDS,这些IDS可能会对有关云中可疑入侵的决策产生负面影响。而且,它们依赖于中央架构在其中管理协作的集中式架构,这与云的分布式性质相矛盾。在本文中,我们提出了一个框架,使IDS能够分布式地形成可信赖的IDS社区。我们基于联盟博弈论设计了一种新颖的分散算法,该算法允许一组基于云的IDS协作建立其联盟,从而即使在存在不受信任的IDS的情况下也可以提高其个体检测的准确性。

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