Alarm reduction and correlation in defence of IP networks

Abstract

Society's critical infrastructures are increasingly dependent on IP networks. Intrusion detection and tolerance within data networks is therefore imperative for dependability in other domains such as telecommunications and future energy management networks. Today's data networks are protected by human operators who are overwhelmed by the massive information overload through false alarm rates of the protection mechanisms. This paper studies the role of alarm reduction and correlation in supporting the security administrator in an enterprise network. We present an architecture that incorporates intrusion detection systems as sensors, and provides improved alarm data to the human operator or to automated actuators. Alarm reduction and correlation via static and adaptive filtering, normalisation, and aggregation is demonstrated on the output from three sensors (Snort, Samhain and Syslog) used in a telecom test network.