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Volumn , Issue , 2007, Pages 83-86

Comparison of two feature selection methods in intrusion detection systems

Author keywords

[No Author keywords available]

Indexed keywords

DATASETS; DECISION DEPENDENT CORRELATION (DDC); QUALITY OF FEATURES;

EID: 38049043908     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIT.2007.4385061     Document Type: Conference Paper
Times cited : (14)

References (11)
  • 1
    • 19944364877 scopus 로고    scopus 로고
    • Chebrolu, S., Abraham, A., and Thomas, J., Feature Deduction and Ensemble Design of Intrusion Detection Systems, Computers and Security, Elsevier Science, 24/4, pp. 295-307, 2005.
    • Chebrolu, S., Abraham, A., and Thomas, J., "Feature Deduction and Ensemble Design of Intrusion Detection Systems", Computers and Security, Elsevier Science, Vol. 24/4, pp. 295-307, 2005.
  • 6
    • 38049031540 scopus 로고    scopus 로고
    • http://kdd.ics.uci.edu/databases/kddcup99/task.html, 2006.
    • (2006)
  • 7
    • 1642355954 scopus 로고    scopus 로고
    • Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context
    • Maheshkumar Sabhnani, Gürsel Serpen: "Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context", MLMTA 2003: 209-215
    • (2003) MLMTA , pp. 209-215
    • Maheshkumar Sabhnani, G.S.1
  • 11
    • 38048998930 scopus 로고    scopus 로고
    • http://www.csie.ntu.edu.tw/~cjlin/libsvm/, 2007.
    • (2007)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.