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Volumn , Issue , 2010, Pages 179-183

Forming an optimal feature set for classifying network intrusions involving multiple feature selection methods

Author keywords

Feature selection; Na ve bayes classifier; Network intrusion detection

Indexed keywords

BAYES CLASSIFIER; CLASSIFICATION RESULTS; COMPUTATIONAL COSTS; DATA SETS; FEATURE SELECTION; FEATURE SELECTION METHODS; FEATURE SETS; FORM FEATURES; MULTIPLE FEATURES; NETWORK DATA; NETWORK INTRUSION DETECTION; NETWORK INTRUSIONS;

EID: 77953897564     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INFRKM.2010.5466923     Document Type: Conference Paper
Times cited : (4)

References (15)
  • 2
    • 34249865012 scopus 로고    scopus 로고
    • Research on intrusion detection and response: A survey
    • P. Kabiri and A.A. Ghorbani, "Research on intrusion detection and response: a survey," International Journal of Network Security, vol. 1, No. 2, 2005, pp.84-102.
    • (2005) International Journal of Network Security , vol.1 , Issue.2 , pp. 84-102
    • Kabiri, P.1    Ghorbani, A.A.2
  • 6
    • 0036532821 scopus 로고    scopus 로고
    • A hybrid filter / wrapper approach of feature selection using information theory
    • M. Sebban and R. Nock, "A hybrid filter / wrapper approach of feature selection using information theory," Pattern Recognition Society, vol. 35, pp.835-846, 2002.
    • (2002) Pattern Recognition Society , vol.35 , pp. 835-846
    • Sebban, M.1    Nock, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.