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

R.J. Hofstede; Aiko Pras

doi:10.1007/978-3-642-30633-4_13

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

R.J. Hofstede, Aiko Pras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

7 Citations (Scopus)

128 Downloads (Pure)

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.

Original language	Undefined
Title of host publication	Proceedings of the 6th International Conference on Autonomous Infrastructure, Management, and Security (AIMS 2012)
Place of Publication	Berlin
Publisher	Springer
Pages	109-112
Number of pages	4
ISBN (Print)	978-3-642-30632-7
DOIs	https://doi.org/10.1007/978-3-642-30633-4_13
Publication status	Published - Jun 2012
Event	6th International Conference on Autonomous Infrastructure, Management, and Security, AIMS 2012 - Luxembourg, Luxembourg Duration: 4 Jun 2012 → 8 Jun 2012

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	7279
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Conference on Autonomous Infrastructure, Management, and Security, AIMS 2012
Period	4/06/12 → 8/06/12
Other	4-8 June 2012

Keywords

METIS-287905
EWI-21998
EC Grant Agreement nr.: FP7/257513
IR-80709

Access to Document

10.1007/978-3-642-30633-4_13

Cite this

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title = "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.",

keywords = "METIS-287905, EWI-21998, EC Grant Agreement nr.: FP7/257513, IR-80709",

author = "R.J. Hofstede and Aiko Pras",

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language = "Undefined",

isbn = "978-3-642-30632-7",

series = "Lecture Notes in Computer Science",

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Hofstede, RJ & Pras, A 2012, Real-Time and Resilient Intrusion Detection: A Flow-Based Approach. in Proceedings of the 6th International Conference on Autonomous Infrastructure, Management, and Security (AIMS 2012). Lecture Notes in Computer Science, vol. 7279, Springer, Berlin, pp. 109-112, 6th International Conference on Autonomous Infrastructure, Management, and Security, AIMS 2012, 4/06/12. https://doi.org/10.1007/978-3-642-30633-4_13

Real-Time and Resilient Intrusion Detection: A Flow-Based Approach. / Hofstede, R.J.; Pras, Aiko.
Proceedings of the 6th International Conference on Autonomous Infrastructure, Management, and Security (AIMS 2012). Berlin: Springer, 2012. p. 109-112 (Lecture Notes in Computer Science; Vol. 7279).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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