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Volumn , Issue , 2003, Pages 209-215

Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context

Author keywords

Computer security; False alarm rate; Intrusion detection; KDD dataset; Machine learning; Misuse; Probability of detection

Indexed keywords

COMPUTER SIMULATION; CONFORMAL MAPPING; DATA PROCESSING; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; PATTERN RECOGNITION; SECURITY OF DATA;

EID: 1642355954     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (210)

References (18)
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    • A Data Mining Framework for Building Intrusion Detection Models
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    • Lee, W.1    Stolfo, S.J.2    Mok, K.W.3
  • 2
    • 0013114810 scopus 로고    scopus 로고
    • Mining in a Data-Flow Environment: Experience in Network Intrusion Detection
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  • 3
    • 1642394649 scopus 로고    scopus 로고
    • KDD data set, 1999; http://kdd.ics.uci.edu/databases/-kddcup99/kddcup99.html
    • (1999) KDD Data Set
  • 4
    • 0013029835 scopus 로고    scopus 로고
    • PNrule: A New Framework for Learning Classifier Models in Data Mining
    • Department of Computer Science, University of Minnesota
    • R. Agarwal, and M. V. Joshi, "PNrule: A New Framework for Learning Classifier Models in Data Mining", Technical Report TR 00-015, Department of Computer Science, University of Minnesota, 2000.
    • (2000) Technical Report , vol.TR 00-015
    • Agarwal, R.1    Joshi, M.V.2
  • 5
    • 1642354876 scopus 로고    scopus 로고
    • KDD-99 Classifier Learning Contest LLSoft's Results Overview
    • ACM SIGKDD, January
    • I. Levin, "KDD-99 Classifier Learning Contest LLSoft's Results Overview", SIGKDD Explorations, ACM SIGKDD, January 2000, Vol. 1 (2), pp. 67-75.
    • (2000) SIGKDD Explorations , vol.1 , Issue.2 , pp. 67-75
    • Levin, I.1
  • 6
    • 26944461753 scopus 로고    scopus 로고
    • Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    • L. Ertoz, M. Steinbach, and V. Kumar, "Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data", Technical Report.
    • Technical Report
    • Ertoz, L.1    Steinbach, M.2    Kumar, V.3
  • 9
    • 0038428854 scopus 로고    scopus 로고
    • Results of the KDD'99 Classifier Learning
    • ACM SIGKDD, Jan
    • C. Elkan, "Results of the KDD'99 Classifier Learning", SIGKDD Explorations, ACM SIGKDD, Jan 2000.
    • (2000) SIGKDD Explorations
    • Elkan, C.1
  • 10
    • 1642383413 scopus 로고    scopus 로고
    • Cited November
    • LNKnet software, http://www.ll.mit.edu/IST/lnknet/-index.html. Cited November 2002.
    • (2002) LNKnet Software
  • 11
    • 1642339383 scopus 로고    scopus 로고
    • Developer: Download code from: http://www.cs.uregina.ca/~dbd/cs831/notes/ml/dtrees/c4.5/tutorial.html. Cited November 2002
    • C4.5 simulator, Developer: http://www.rulequest-.com; Download code from: http://www.cs.uregina.ca/~dbd/cs831/notes/ml/dtrees/c4.5/tutorial.html. Cited November 2002.
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  • 18
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    • Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps
    • G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, & D. B. Rosen, "Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps", IEEE Trans. on Neural Networks, 1992, Vol. 3, pp. 698 - 713.
    • (1992) IEEE Trans. on Neural Networks , vol.3 , pp. 698-713
    • Carpenter, G.A.1    Grossberg, S.2    Markuzon, N.3    Reynolds, J.H.4    Rosen, D.B.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.