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Instantiated First Order Qualitative Choice Logic for an efficient handling of alerts correlation

机译:实例化的一阶定性选择逻辑可有效处理警报关联

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Intrusion Detection Systems (IDS) are necessary and important tools for monitoring information systems. However they produce a huge quantity of alerts. Alerts correlation is a process that reduces the number of alerts reported by intrusion detection systems. In this paper, we propose a new algorithm for a logical-based alerts correlation approach that integrates: security operator's knowledge and preferences. The representation and the reasoning on these knowledge and preferences are done using a new logic called Instantiated First Order Qualitative Choice Logic (IFO-QCL). Our modeling views an alert as an interpretation which allows us to have an efficient algorithm that performs the correlation process in a polynomial time. This paper also provides experimental results which are achieved on datasets issued from a real monitoring system.
机译:入侵检测系统(IDS)是监视信息系统的必要和重要工具。但是,它们会产生大量警报。警报关联是一个减少入侵检测系统报告的警报数量的过程。在本文中,我们为基于逻辑的警报关联方法提出了一种新算法,该算法集成了:安全操作员的知识和偏好。这些知识和偏好的表示以及推理是使用称为“实例化一阶定性选择逻辑”(IFO-QCL)的新逻辑完成的。我们的建模将警报视为一种解释,这使我们可以拥有一个有效的算法,该算法可以在多项式时间内执行相关过程。本文还提供了从真实监控系统发布的数据集获得的实验结果。

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