Optimization of intrusion detection through fast hybrid feature selection

Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings

Volumn 2005, Issue , 2005, Pages 264-266

  Shazzad, Khaja Mohammad ^a   Park, Jong Sou ^a  

^a Hankuk Aviation University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE SELECTION METHODS; INTRUSION DETECTIONS; SUPPORT VECTOR MACHINES;

DECISION MAKING; GENETIC ALGORITHMS; MATHEMATICAL MODELS; PERSONNEL TRAINING;

FEATURE EXTRACTION;

EID: 33745122959     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PDCAT.2005.181     Document Type: Conference Paper

References (8)

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3. Dash M., Liu H., & Motoda H, "Consistency based feature selection", Proc. of the Fourth PAKDD 2000, Kyoto, Japan, 2000, pp. 98-109.
4. H. Almuallim and T.G. Dietterich" "Learning Boolean Concepts in the Presence of Many Irrelevant Features", Artificial Intelligence, vol. 69, nos. 1-2, 1994, pp. 279-305.
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6. Dong Seong Kim, Ha-Nam Nguyen, Syng-Yup Ohn, Jong Sou Park, "Fusions of GA and SVM for Anomaly Detection in Intrusion Detection System", ISNN (3) 2005, pp. 415-420.
7. A. H. Sung, S. Mukkamala, "Identifying Important Features for Intrusion Detection Using Support Vector Machines and Neural Networks" Proc. of the International Symposium on Applications and the Internet Technology, IEEE Computer Society Press, 2003, pp. 209-216.
8. Vapnik, V., The Nature of Statistical Learning Theory, Springer, Berlin Heidelberg New York, 1995.