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Volumn 1, Issue , 2008, Pages 1162-1167

Anomaly Intrusion Detection System using Gaussian Mixture Model

Author keywords

Anomaly detection; Gaussian Mixture Model; Intrusion Detection; Pattern matching

Indexed keywords

BLIND SOURCE SEPARATION; COMMUNICATION CHANNELS (INFORMATION THEORY); COMPUTER CRIME; COMPUTER NETWORKS; DISTRIBUTION FUNCTIONS; IMAGE SEGMENTATION; INFORMATION TECHNOLOGY; MIXTURES; OBJECT RECOGNITION; PATTERN MATCHING; PROBABILITY DISTRIBUTIONS; SECURITY OF DATA; TRELLIS CODES;

EID: 57849141227     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCIT.2008.17     Document Type: Conference Paper
Times cited : (27)

References (9)
  • 1
    • 57849121556 scopus 로고    scopus 로고
    • A Secure and Efficient Model for Network Defensive Systems
    • Dec, Taiwan
    • H. Lin, C. Jiang, H. Huang, "A Secure and Efficient Model for Network Defensive Systems", ICS Dec 2006, Taiwan.
    • (2006) ICS
    • Lin, H.1    Jiang, C.2    Huang, H.3
  • 3
    • 0002365658 scopus 로고    scopus 로고
    • Learning Program Behavior Profiles for Intrusion Detection
    • A. K. Ghosh, "Learning Program Behavior Profiles for Intrusion Detection". USENIX 1999.
    • (1999) USENIX
    • Ghosh, A.K.1
  • 4
    • 57849137387 scopus 로고    scopus 로고
    • Lincoln Laboratory, DARPA Intrusion Detection Evaluation
    • Lincoln Laboratory, Massachusetts Institute of Technology (MIT), 1998-2000. DARPA Intrusion Detection Evaluation.
    • (1998) Massachusetts Institute of Technology (MIT)
  • 7
    • 33744768841 scopus 로고    scopus 로고
    • An Alternative Extension Of The K-Means Algorithm for Clustering Categorical Data
    • O.M. San, V.N. Huynh, and Y. Nakamori, "An Alternative Extension Of The K-Means Algorithm for Clustering Categorical Data", Int. J. Appl. Math. Comput. Sci. Vol. 14, No. 2, 241-247, 2004.
    • (2004) Int. J. Appl. Math. Comput. Sci , vol.14 , Issue.2 , pp. 241-247
    • San, O.M.1    Huynh, V.N.2    Nakamori, Y.3
  • 9
    • 57849120656 scopus 로고    scopus 로고
    • http://kdd.ics.uci.edu/databases/kddcup99/task.html


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.