多智能体系统运行时攻击检测的图分析方法

Jan Kantert, H. Scharf, Sarah Edenhofer, Sven Tomforde, J. Hähner, C. Müller-Schloer
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引用次数: 16

摘要

由各种异构和自治实体组成的完全自组织和开放系统可能受到恶意元素或攻击。应对这一挑战的一种方法是引入信任。因此,信任关系基于个体实体之间的评级,并表示系统范围的信息。可信桌面计算网格就是一个例子,其中成功地应用了这种信任机制。在本文中,我们研究了在自组织系统中添加系统级观察者的可能性,以便指导整体行为并干预主要由恶意行为引起的干扰情况。因此,我们详细描述了如何实现这个观察者的观察部分,以及可以应用哪种度量来检测不希望的系统行为。评估使用可信桌面网格完成,并演示了通过考虑可信实体集群快速可靠地检测恶意行为的可能性。
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A Graph Analysis Approach to Detect Attacks in Multi-agent Systems at Runtime
Fully self-organised and open systems consisting of a variety of heterogeneous and autonomous entities can suffer due to malicious elements or attacks. One approach to cope with this challenge is to introduce trust. Thereby, trust relationships are based on ratings among individual entities and represent system-wide information. A Trusted Desktop Computing Grid is one example, where such a trust mechanism has been applied successfully. In this paper, we investigate the possibility to add an system-level Observer to the self-organised system in order to guide the overall behaviour and to intervene in disturbed situations that are mostly a result of malicious behaviour. Therefore, we describe in detail how the observation part of this Observer can be realised and what kind of metrics can be applied to detect undesired system behaviour. Evaluations are done using the Trusted Desktop Grid and demonstrate the possibility to detect malicious behaviour quickly and reliably by considering clusters of trusted entities.
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