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

Abstract

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.