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Volumn 1, Issue , 2009, Pages 150-152

The application on intrusion detection based on K-means cluster algorithm

Author keywords

Cluster; Clustering analysis; Intrusion detection; K means algorithm

Indexed keywords

ANOMALY DETECTION; CLUSTER; CLUSTER ALGORITHMS; CLUSTERING ANALYSIS; COMPUTING SYSTEM; DATA MINING TECHNIQUES; INTERNET SECURITY; K-MEANS; K-MEANS ALGORITHM; NETWORK INTRUSION DETECTION; OR-NETWORKS; REAL NETWORKS; UNLABELED DATA;

EID: 70350528581     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IFITA.2009.34     Document Type: Conference Paper
Times cited : (118)

References (7)
  • 1
    • 0032090765 scopus 로고    scopus 로고
    • Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. Proc
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    • R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. Proc. ACM SIGMOD, June 1998: 94-105
    • (1998) ACM SIGMOD , pp. 94-105
    • Agrawal, R.1    Gehrke, J.2    Gunopulos, D.3    Raghavan, P.4
  • 2
    • 0002048998 scopus 로고
    • AValidation Study of a Variable Weighting Algorithm for Cluster Analysis
    • G. Milligan. AValidation Study of a Variable Weighting Algorithm for Cluster Analysis. J. Classification 1989: 53-71
    • (1989) J. Classification , pp. 53-71
    • Milligan, G.1
  • 5
    • 70350554353 scopus 로고    scopus 로고
    • Jiangtao Ren, Xiaoxiao Shi. An. Improved K-Means Clustering Algorithm Based on Feature Weighting [J]. Computer Science, 2006, 33(7): 186-187
    • Jiangtao Ren, Xiaoxiao Shi. An. Improved K-Means Clustering Algorithm Based on Feature Weighting [J]. Computer Science, 2006, 33(7): 186-187
  • 7
    • 70350532806 scopus 로고    scopus 로고
    • E. Eskin, A. Arnold, M. Prerau, L. Portnoy, S. Stolfo. A. Geometric. Framw ork for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data. Application of Data Mining in Computer Security, Kluwer, 2002
    • E. Eskin, A. Arnold, M. Prerau, L. Portnoy, S. Stolfo. A. Geometric. Framw ork for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data. Application of Data Mining in Computer Security, Kluwer, 2002


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.