Research of intrusion detection based on support vector machine

Proceedings - 2008 International Conference on Advanced Computer Theory and Engineering, ICACTE 2008

Volumn , Issue , 2008, Pages 434-438

  Zhu, Gengming ^a   Liao, Junguo ^a  

^a HUNAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; SUPPORT VECTOR MACHINES;

ENHANCE LEARNING; INTRUSION DETECTION METHODS; LEARNING SPEED; LOCAL DENSITIES; NETWORK DATUM; SAMPLE DENSITIES; SVM ALGORITHMS; TRAINING SAMPLES;

INTRUSION DETECTION;

EID: 62949217752     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICACTE.2008.132     Document Type: Conference Paper

References (8)

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3. WLee, S J Stolfo and PKChan, "Learning patterns from UNIX processes execution traces for intrusion detection", In AAAI Workshop on AI Approaches to Fraud Detection and Risk Management, AAAi Press, 1997.
4. V.N.VaPnik, Statistical Learning Theory, John Wiley and Sons, 1998
5. T.Joaehims, "Text categorization with support vector machines", Proc.10th European Conference on Machine Learning, Chemnitz, Germany, 1998.
6. Support vector machines software, http://www.support-vecetor-maehines. org/SVM-soft.htlnl.
7. D.Denning, "An intrusion detection model", IEEE Transactions On Software Engineering, 1987, 13(2):222-232.
8. V.VaPnik, "Estimation of Dependences Based on Empirical Data", Berlin: SPringer-Verlag, 1982.