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Volumn , Issue , 2012, Pages 1957-1960

Fusion of BVM and ELM for anomaly detection in computer networks

Author keywords

Anomaly detection; Ball vector machine; Data fusion; Extreme learning machine

Indexed keywords

ANOMALY DETECTION; BP NEURAL NETWORKS; DATA SETS; DETECTION RATES; EXTREME LEARNING MACHINE; FALSE ALARM RATE; FUSION METHODS; NETWORK ANOMALY DETECTION; TRAINING TIME; VECTOR MACHINES;

EID: 84873865040     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSSS.2012.488     Document Type: Conference Paper
Times cited : (4)

References (11)
  • 1
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    • A neural network component for an intrusion detection system
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    • DEBAR H, BECKER M, SIBONI D. A neural network component for an intrusion detection system. proceedings of the Research in Security and Privacy, 1992 Proceedings, 1992 IEEE Computer Society Symposium on, F 4-6 May 1992.
    • (1992) Proceedings of the Research in Security and Privacy
    • Debar, H.1    Becker, M.2    Siboni, D.3
  • 3
    • 62949217752 scopus 로고    scopus 로고
    • Research of intrusion detection based on support vector machine
    • ICACTE '08 International Conference on, F 20-22 Dec. 2008
    • GENGMING Z, JUNGUO L. Research of Intrusion Detection Based on Support Vector Machine. proceedings of the Advanced Computer Theory and Engineering, 2008 ICACTE '08 International Conference on, F 20-22 Dec. 2008.
    • (2008) Proceedings of the Advanced Computer Theory and Engineering
    • Gengming, Z.1    Junguo, L.2
  • 4
    • 84866007605 scopus 로고    scopus 로고
    • Fusion of SVM and BMPM for anomaly detection in computer networks
    • WANG H, LIU Y. Fusion of SVM and BMPM for anomaly detection in computer networks.computer Engineering and Design, 2011, 32 (5): 1601-4.
    • (2011) Computer Engineering and Design , vol.32 , Issue.5 , pp. 1601-1604
    • Wang, H.1    Liu, Y.2
  • 5
    • 35348821822 scopus 로고    scopus 로고
    • Intrusion detection in computer networks by a modular ensemble of one-class classifiers
    • GIACINTO G, PERDISCI R, DEL RIO M, et al. Intrusion detection in computer networks by a modular ensemble of one-class classifiers. Information Fusion, 2008, 9 (1): 69-82.
    • (2008) Information Fusion , vol.9 , Issue.1 , pp. 69-82
    • Giacinto, G.1    Perdisci, R.2    Del Rio, M.3
  • 6
    • 33745903481 scopus 로고    scopus 로고
    • Extreme learning machine: Theory and applications
    • HUANG G, ZHU Q, SIEW C. Extreme learning machine: Theory and applications. Neurocomputing, 2006, 70 (1-3): 489-501.
    • (2006) Neurocomputing , vol.70 , Issue.1-3 , pp. 489-501
    • Huang, G.1    Zhu, Q.2    Siew, C.3
  • 8
    • 77949290310 scopus 로고    scopus 로고
    • Comparison of extreme learning machine with support vector regression for reservoir permeability prediction
    • CIS '09 International Conference on, F 11-14 Dec. 2009
    • GUO-JIAN C, LEI C, HUA-XIAN P.comparison of Extreme Learning Machine with Support Vector Regression for Reservoir Permeability Prediction. proceedings of the Computational Intelligence and Security, 2009 CIS '09 International Conference on, F 11-14 Dec. 2009.
    • (2009) Proceedings of the Computational Intelligence and Security
    • Guo-Jian, C.1    Lei, C.2    Hua-Xian, P.3
  • 10
    • 0038330235 scopus 로고    scopus 로고
    • Fusion of multiple classifiers for intrusion detection in computer networks
    • GIACINTO G. Fusion of multiple classifiers for intrusion detection in computer networks. Pattern Recognition Letters, 2003, 24 (12): 1795-803.
    • (2003) Pattern Recognition Letters , vol.24 , Issue.12 , pp. 1795-1803
    • Giacinto, G.1
  • 11
    • 80051793908 scopus 로고    scopus 로고
    • Data preprocessing for anomaly based network intrusion detection: A review
    • DAVIS J J, CLARK A J. Data preprocessing for anomaly based network intrusion detection: A review.computers & Security, 2011, 30 (6-7): 353-75.
    • (2011) Computers & Security , vol.30 , Issue.6-7 , pp. 353-375
    • Davis, J.J.1    Clark, A.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.