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Rule Generalisation in Intrusion Detection Systems using Snort

Aickelin, Uwe; Twycross, Jamie; Hesketh-Roberts, Thomas

Authors

Uwe Aickelin

Jamie Twycross

Thomas Hesketh-Roberts



Abstract

Intrusion Detection Systems (IDSs) provide an important
layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An IDS’s responsibility is to detect suspicious or unacceptable system and network activity and to alert a systems administrator to this activity. The majority of IDSs use a set of signatures that define what suspicious traffic is, and Snort is one popular and actively developing open-source IDS that uses such a set of signatures known as Snort rules. Our aim is to identify a way in which Snort could be developed further by generalising rules to identify novel attacks. In particular, we attempted to relax and vary the conditions and parameters of current Snort rules, using a similar approach to classic rule learning operators such as generalisation and specialisation. We demonstrate the effectiveness of our approach through experiments with standard datasets and
show that we are able to detect previously undetected variants of various attacks. We conclude by discussing the general effectiveness and appropriateness of generalisation in Snort based IDS rule processing.

Keywords: anomaly detection, intrusion detection, Snort, Snort rules

Journal Article Type Article
Journal International Journal of Electronic Security and Digital Forensics
Print ISSN 1751-911X
Publisher Inderscience
Peer Reviewed Peer Reviewed
Volume 1
Issue 1
APA6 Citation Aickelin, U., Twycross, J., & Hesketh-Roberts, T. Rule Generalisation in Intrusion Detection Systems using Snort. International Journal of Electronic Security and Digital Forensics, 1(1), doi:10.1504/IJESDF.2007.013596
DOI https://doi.org/10.1504/IJESDF.2007.013596
Publisher URL http://www.inderscience.com/storage/f785311121421069.pdf
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information (c) Inderscience 2007

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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