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Real-Time and Resilient Intrusion Detection: A Flow-Based Approach

Abstract : Flow-based intrusion detection will play an important role in high-speed networks, due to the stringent performance requirements of packet-based solutions. Flow monitoring technologies, such as NetFlow or IPFIX, aggregate individual packets into flows, requiring new intrusion detection algorithms to deal with the aggregated data. These algorithms are subject to constraints on real-time and accurate detection of intrusions, due to the nature of current flow monitoring technologies. In this paper, we propose a framework for flow-based intrusion detection, aiming to detect intrusions in real-time, and to be resilient against negative effects of attacks on monitoring systems. This research is still in its initial phase and will contribute to a Ph.D. thesis after four years.
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Rick Hofstede, Aiko Pras. Real-Time and Resilient Intrusion Detection: A Flow-Based Approach. 6th International Conference on Autonomous Infrastructure (AIMS), Jun 2012, Luxembourg, Luxembourg. pp.109-112, ⟨10.1007/978-3-642-30633-4_13⟩. ⟨hal-01529793⟩

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