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

机译:多云环境中的基于信任的基于基于的游戏理论模型

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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,易受攻击。网络攻击也变得更加复杂,更难以检测。因此,由于对攻击的有限和知识不完全,因此越来越困难地检测到所有攻击,以检测所有攻击。最近在网络安全的研究表明,IDS之间的合作可以在这种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ID可以咨询关于可疑入侵的其他IDS,并提高决策准确性。现有合作IDS方法的问题是,他们忽略了不受信任的(恶意或没有)IDS,这可能会对云中可疑入侵的决定产生负面影响。此外,他们依靠中央代理规范合作的集中架构,这与云的分布性质相矛盾。在本文中,我们提出了一个框架,使IDS能够分散地形成值得信赖的IDS社区。我们基于独立博弈论设计了一种新颖的分散算法,允许一组基于云的IDS合作地建立他们的联盟,即使在存在不受信任的IDS的情况下,即使在存在不受信任的IDS中,也可以使其个人检测精度增加。

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