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Volumn 58, Issue 2-3, 2005, Pages 217-230

Principle components and importance ranking of distributed anomalies

Author keywords

Anomaly detection; Machine learning

Indexed keywords

COMPUTER SYSTEMS; DATA MINING; EIGENVALUES AND EIGENFUNCTIONS; LEARNING SYSTEMS; LOCAL AREA NETWORKS; SECURITY OF DATA; TIME SERIES ANALYSIS;

EID: 15544363043     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10994-005-5827-4     Document Type: Article
Times cited : (16)

References (25)
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  • 9
    • 30344486259 scopus 로고    scopus 로고
    • Probabilistic anomaly detection in distributed computer networks
    • (resubmitted)
    • Burgess, M. (resubmitted). Probabilistic anomaly detection in distributed computer networks. Science of Computer Programming.
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  • 16
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    • Authoritative sources in a hyperlinked environment
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  • 17
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  • 23
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    • A survey of fault localization techniques in computer networks
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    • Steinder, M. & Sethi, A. (2003). A survey of fault localization techniques in computer networks. Science of Computer Programming (to appear).
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  • 24
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    • Data mining-based intrusion detectors: An overview of the columbia IDS project
    • Stolfo, S. J., Lee, W., Chan, P. K., Fan, W., & Eskin, E. (2001). Data mining-based intrusion detectors: An overview of the columbia IDS project. ACM SIGMOD, 30:4.
    • (2001) ACM SIGMOD , vol.30 , pp. 4
    • Stolfo, S.J.1    Lee, W.2    Chan, P.K.3    Fan, W.4    Eskin, E.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.