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Volumn , Issue , 2005, Pages

Selecting features for intrusion detection: A feature relevance analysis on KDD 99 intrusion detection datasets

Author keywords

Feature relevance; Information gain; Intrusion detection; KDD 99 intrusion detection datasets

Indexed keywords

DETECTION RATES; FALSE POSITIVE RATES; FEATURE RELEVANCE; INFORMATION GAIN; KDD 99 INTRUSION DETECTION DATASETS; LABELED DATA; LABELED DATASET; TRAINING DATA;

EID: 84883271942     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (215)

References (13)
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    • Testing intrusion detection systems: A critique of the 1998 and 1999 darpa intrusion detection system evaluations as performed by lincoln laboratory
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    • Pfahringer B. Winning the KDD99 Classification Cup: Bagged Boosting. SIGKDD Explorations, 1(2):65-66, 2000.
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    • Pfahringer, B.1
  • 5
    • 1642354876 scopus 로고    scopus 로고
    • KDD-99 classifier learning contest: Llsoft's results overview
    • Levin I. KDD-99 Classifier Learning Contest: LLSoft's Results Overview. SIGKDD Explorations, 1(2):67-75, 2000.
    • (2000) SIGKDD Explorations , vol.1 , Issue.2 , pp. 67-75
    • Levin, I.1
  • 7
    • 0033295259 scopus 로고    scopus 로고
    • Bro: A system for detecting network intruders in real-time
    • 14 Dec.
    • Paxson V., "Bro: A System for Detecting Network Intruders in Real-Time", Computer Networks, 31(23-24), pp. 2435-2463, 14 Dec. 1999.
    • (1999) Computer Networks , vol.31 , Issue.23-24 , pp. 2435-2463
    • Paxson, V.1
  • 8
    • 0003704318 scopus 로고    scopus 로고
    • Irvine, CA: University of California, Department of Information and Computer Science
    • S. Hettich, S.D. Bay, The UCI KDD Archive. Irvine, CA: University of California, Department of Information and Computer Science, http://kdd.ics.uci. edu, 1999.
    • (1999) The UCI KDD Archive
    • Hettich, S.1    Bay, S.D.2
  • 10
    • 49649112245 scopus 로고    scopus 로고
    • Why machine learning algorithms fail in misuse detection on KDD intrusion detection data set
    • Sabhnani M., Serpen G., "Why Machine Learning Algorithms Fail in Misuse Detection on KDD Intrusion Detection Data Set", In Journal of Intelligent Data Analysis, 2004.
    • (2004) Journal of Intelligent Data Analysis
    • Sabhnani, M.1    Serpen, G.2
  • 11
    • 0141797880 scopus 로고    scopus 로고
    • A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data
    • Chapter 4, D. Barbara and S. Jajodia (editors), Kluwer, ISBN 1-4020-7054-3
    • E. Eskin, A. Arnold, M. Prerau, L. Portnoy, S. Stolfo, "A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data, " in Applications of Data Mining in Computer Security, Chapter 4, D. Barbara and S. Jajodia (editors), Kluwer, ISBN 1-4020-7054-3, 2002.
    • (2002) Applications of Data Mining in Computer Security
    • Eskin, E.1    Arnold, A.2    Prerau, M.3    Portnoy, L.4    Stolfo, S.5
  • 12
    • 34748822627 scopus 로고    scopus 로고
    • Analysis of three intrusion detection system benchmark datasets using machine learning algorithms
    • Atlanta, USA, May
    • Kayacik, G. H., Zincir-Heywood, A. N., "Analysis of Three Intrusion Detection System Benchmark Datasets Using Machine Learning Algorithms", Proceedings of the IEEE ISI 2005 Atlanta, USA, May 2005.
    • (2005) Proceedings of the IEEE ISI 2005
    • Kayacik, G.H.1    Zincir-Heywood, A.N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.