10.1016/j.cose.2017.10.011

10.1016/j.cose.2017.10.011 computers & security 73 (2018) 137–155 Available online at www.sciencedirect.com ScienceDirect journal homepage: www.elsevier.com/locate/cose Network intrusion detection system based on recursive feature addition and bigram technique Tarfa Hamed *, Rozita Dara, Stefan C. Kremer School of Computer Science, University of Guelph, Guelph, ON, Canada AR TICLE INFO ABSTRA CT Article history: Network and Internet security is a critical universal issue. The increased rate of cyber ter- Received 24 April 2017 rorism has put national security under risk. In addition, Internet attacks have caused severe Received in revised form 4 October damages to different sectors (i.e., individuals, economy, enterprises, organizations and gov- 2017 ernments). Network Intrusion Detection Systems (NIDS) are one of the solutions against these Accepted 27 October 2017 attacks. However, NIDS always need to improve their performance in terms of increasing Available online 14 November 2017 the accuracy and decreasing false alarms. Integrating feature selection with intrusion de- tection has shown to be a successful approach since feature selection can help in selecting Keywords: the most informative features from the entire set of features. Feature selection Usually, for the stealthy and low profile attacks (zero – day attacks), there are few neatly Intrusion detection concealed packets distributed over http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

10.1016/j.cose.2017.10.011

Elsevier — Jun 11, 2020

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computers & security 73 (2018) 137–155 Available online at www.sciencedirect.com ScienceDirect journal homepage: www.elsevier.com/locate/cose Network intrusion detection system based on recursive feature addition and bigram technique Tarfa Hamed *, Rozita Dara, Stefan C. Kremer School of Computer Science, University of Guelph, Guelph, ON, Canada AR TICLE INFO ABSTRA CT Article history: Network and Internet security is a critical universal issue. The increased rate of cyber ter- Received 24 April 2017 rorism has put national security under risk. In addition, Internet attacks have caused severe Received in revised form 4 October damages to different sectors (i.e., individuals, economy, enterprises, organizations and gov- 2017 ernments). Network Intrusion Detection Systems (NIDS) are one of the solutions against these Accepted 27 October 2017 attacks. However, NIDS always need to improve their performance in terms of increasing Available online 14 November 2017 the accuracy and decreasing false alarms. Integrating feature selection with intrusion de- tection has shown to be a successful approach since feature selection can help in selecting Keywords: the most informative features from the entire set of features. Feature selection Usually, for the stealthy and low profile attacks (zero – day attacks), there are few neatly Intrusion detection concealed packets distributed over

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