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Volumn 71, Issue 16-18, 2008, Pages 3247-3252

High-order Markov kernels for intrusion detection

Author keywords

Intrusion detection; Markov kernels; String kernels; Suffix tree

Indexed keywords

COMPUTER CRIME; MARKOV PROCESSES; NEURAL NETWORKS; SECURITY OF DATA; SIGNAL DETECTION; SUPPORT VECTOR MACHINES; TREES (MATHEMATICS);

EID: 56549097799     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.04.041     Document Type: Conference Paper
Times cited : (17)

References (20)
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    • E. Eskin, A. Arnold, M. Prerau, L. Portnoy, and S. Stolfo A geometric framework for unsupervised anomaly detection: detecting intrusions in unlabeled data D. Barbara S. Jajodia Applications of Data Mining in Computer Security 2002 Kluwer Academic Publishers Netherlands
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    • Eskin, E.1    Arnold, A.2    Prerau, M.3    Portnoy, L.4    Stolfo, S.5
  • 5
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    • Predicting the intrusion intentions by observing system call sequences
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    • R. Giegerich, and S. Kurtz From Ukkonen to McCreight and Weiner: a unifying view of linear-time suffix tree construction Algorithmica 19 3 1997 331 353
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    • Giegerich, R.1    Kurtz, S.2
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    • A hybrid high-order Markov chain model for computer intrusion detection
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    • Host-based intrusion detection using dynamic and static behavioral models
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.