Comparative study of supervised machine learning techniques for intrusion detection

Proceedings - CNSR 2007: Fifth Annual Conference on Communication Networks and Services Research

Volumn , Issue , 2007, Pages 350-355

  Gharibian, Farnaz ^a   Ghorbani, Ali A ^a  

^a UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; INTRUSION DETECTION; NETWORK SECURITY; PROBABILISTIC LOGICS; PROBLEM SOLVING;

INTRUSION DETECTION RATE; STANDARD DEVIATIONS; TRAINING DATASETS;

SUPERVISED LEARNING;

EID: 34548359129     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CNSR.2007.22     Document Type: Conference Paper

References (11)

1. Available at http://kdd.ics.uci.edu//databases/kddcup99/kddcup99.html.
2. N. B. Amor, S. Benferhat, and Z. Elouedi. Naive bayes vs decision trees in intrusion detection systems, pages 420-424, 2004.
3. L. Breiman. Random forests. Machine Learning, 45(1):5-32, October 2001.
4. P. Chan, M. Mahoney, and M. Arshad. Learning rules and clusters for anomaly detection in network traffic. Managing Cyber Threats: Issues, Approaches and Challenges, pages 81-99, 2003.
5. R. Gopinath. Maximum likelihood modeling with gaussian distributions for classification, 1998.
6. G. H. John and P. Langley. Estimating continuous distributions in bayesian classifiers. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, pages 338-345, 1995.
7. Z. S. Pan, S. C. Chen, G. B. Hu, and D. Q. Zhang. Hybrid neural network and c4.5 for misuse detection. International Conference on Machine Learning and Cybernetics, 4:2463-2467, 2-5 Nov. 2003.
8. J. R. Quinlan. C4.5, Programs for machine learning. Morgan Kaufmann San Mateo Ca, 1993.
9. M. Sabhnani and G. Serpen. In Proceedings of the International Conference on Machine Learning, Models, Technologies and Applications (MLMTA 2003).
10. G. Stein, B. Chen, A. S. Wu, and K. A. Hua. Decision tree classifier for network intrusion detection with ga-based feature selection. In ACM-SE 43:Proceedings of the 43rd annual southeast regional conference, pages 136-141, New York, NY, USA, 2005. ACM Press.
11. J. Zhang and M. Zulkernine. Network intrusion detection using random forests. Proceedings of the the Third Annual Conference on Privacy, Security and Trust, pages 53-61, October 2005.