메뉴 건너뛰기




Volumn 26, Issue 6, 2005, Pages 779-791

Intrusion detection using hierarchical neural networks

Author keywords

BackPropagation algorithm; Hierarchical neural network; Intrusion detection; Neural network ensembles; Neural networks; Radius basis functions

Indexed keywords

ALGORITHMS; BACKPROPAGATION; CRYPTOGRAPHY; DETECTORS; HIERARCHICAL SYSTEMS; LEARNING SYSTEMS; NEURAL NETWORKS; REAL TIME SYSTEMS;

EID: 15944375471     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2004.09.045     Document Type: Article
Times cited : (151)

References (26)
  • 1
    • 0004048154 scopus 로고
    • Computer security threat monitoring and surveillance
    • James P. Anderson Company, Fort Washington, PA, April 1980
    • Anderson, J.P., 1980. Computer security threat monitoring and surveillance. Technical Report, James P. Anderson Company, Fort Washington, PA, April 1980
    • (1980) Technical Report
    • Anderson, J.P.1
  • 2
    • 84928016636 scopus 로고    scopus 로고
    • The base-rate fallacy and the difficulty of intrusion detection
    • S. Axelsson The base-rate fallacy and the difficulty of intrusion detection ACM Trans. Inform. System Security 3 3 2000 186 205
    • (2000) ACM Trans. Inform. System Security , vol.3 , Issue.3 , pp. 186-205
    • Axelsson, S.1
  • 3
    • 0003516333 scopus 로고    scopus 로고
    • Intrusion detection systems: A survey and taxonomy
    • Chalmers University, March
    • Axelsson, S., 2000b. Intrusion detection systems: A survey and taxonomy. Technical Report 99-15, Chalmers University, March
    • (2000) Technical Report , vol.99 , Issue.15
    • Axelsson, S.1
  • 6
    • 0036588773 scopus 로고    scopus 로고
    • Incorporating soft computing techniques into a probabilistic intrusion detection system
    • S.-B. Cho Incorporating soft computing techniques into a probabilistic intrusion detection system IEEE Trans. Systems Man Cybernet. 32 2 2002 154
    • (2002) IEEE Trans. Systems Man Cybernet. , vol.32 , Issue.2 , pp. 154
    • Cho, S.-B.1
  • 9
    • 85036529638 scopus 로고    scopus 로고
    • Intrusion detection: Applying machine learning to solaris audit data
    • Los Alamitos, CA
    • Endler, D., 1998. Intrusion detection: Applying machine learning to solaris audit data. In: Proc. 1998 Annual Computer Security Applications Conf., Los Alamitos, CA, pp. 268-279
    • (1998) Proc. 1998 Annual Computer Security Applications Conf. , pp. 268-279
    • Endler, D.1
  • 11
    • 85019678573 scopus 로고    scopus 로고
    • Detecting anomalous and unknown intrusions against programs
    • Los Alamitos, CA, USA, December 1998. IEEE Comput. Soc. 1998
    • Ghosh, A., Wanken, J., Charron, F., 1998. Detecting anomalous and unknown intrusions against programs. In: Proc. 1998 Annual Computer Security Applications Conf., ACSAC'98, Los Alamitos, CA, USA, December 1998. IEEE Comput. Soc. 1998, 259-267
    • (1998) Proc. 1998 Annual Computer Security Applications Conf., ACSAC'98 , pp. 259-267
    • Ghosh, A.1    Wanken, J.2    Charron, F.3
  • 13
    • 0038330235 scopus 로고    scopus 로고
    • Fusion of multiple classifiers for intrusion detection in computer networks
    • G. Giacinto, F. Roli, and L. Didaci Fusion of multiple classifiers for intrusion detection in computer networks Pattern Recognition Lett. 24 12 2003 1795
    • (2003) Pattern Recognition Lett. , vol.24 , Issue.12 , pp. 1795
    • Giacinto, G.1    Roli, F.2    Didaci, L.3
  • 14
    • 15944401308 scopus 로고    scopus 로고
    • The Distributed Systems Group in the Information Systems Institute of Technical University of Vienna, October
    • Gordeev, M., 2000. Intrusion detection: Techniques and approaches. The Distributed Systems Group in the Information Systems Institute of Technical University of Vienna, October
    • (2000) Intrusion Detection: Techniques and Approaches
    • Gordeev, M.1
  • 15
    • 0010818929 scopus 로고    scopus 로고
    • Computer system intrusion detection: A survey
    • Computer Science Department, University of Virginia
    • Jones, A.K., Sielken, R.S., 1999. Computer system intrusion detection: A survey. Technical Report, Computer Science Department, University of Virginia
    • (1999) Technical Report
    • Jones, A.K.1    Sielken, R.S.2
  • 17
    • 0035402096 scopus 로고    scopus 로고
    • Training a neural-network based intrusion detector to recognize novel attacks, systems, man and cybernetics
    • Computer Press
    • Lee, H.D., S.C., 2001. Training a neural-network based intrusion detector to recognize novel attacks, systems, man and cybernetics, Part A IEEE Transactions on IEEE Computer Press 31, 294-299
    • (2001) Part A IEEE Transactions on IEEE , vol.31 , pp. 294-299
    • Lee, H.D.1    C., S.2
  • 18
    • 0032630098 scopus 로고    scopus 로고
    • Detecting computer and network misuse through the production-based expert system toolset (p-BEST)
    • Lindqvist, U., Porras, P.A., 1999. Detecting computer and network misuse through the production-based expert system toolset (p-BEST). In: IEEE Symposium on Security and Privacy, pp. 146-161
    • (1999) IEEE Symposium on Security and Privacy , pp. 146-161
    • Lindqvist, U.1    Porras, P.A.2
  • 19
    • 0036804085 scopus 로고    scopus 로고
    • Network intrusion and fault detection: A statistical anomaly approach
    • C. Manikopoulos, and S. Papavassiliou Network intrusion and fault detection: A statistical anomaly approach Commun. Mag. IEEE 40 10 2002 76 82
    • (2002) Commun. Mag. IEEE , vol.40 , Issue.10 , pp. 76-82
    • Manikopoulos, C.1    Papavassiliou, S.2
  • 26
    • 0028385414 scopus 로고
    • Fuzzy logic, neural networks, and soft computing
    • L.A. Zadeh Fuzzy logic, neural networks, and soft computing Commun. ACM 37 1994 77 84
    • (1994) Commun. ACM , vol.37 , pp. 77-84
    • Zadeh, L.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.