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Volumn 3498, Issue III, 2005, Pages 415-420

Fusions of GA and SVM for anomaly detection in intrusion detection system

Author keywords

[No Author keywords available]

Indexed keywords

ERROR DETECTION; MATHEMATICAL MODELS; OPTIMIZATION;

EID: 24944485860     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11427469_67     Document Type: Conference Paper
Times cited : (52)

References (16)
  • 1
    • 84960354764 scopus 로고    scopus 로고
    • Gene selection for cancer classification using bootstrapped genetic algorithms and support vector machines
    • Chen, X.: Gene Selection for Cancer Classification Using Bootstrapped Genetic Algorithms and Support Vector Machines. The Computational Systems Bioinformatics Conference (2003) 504-505.
    • (2003) The Computational Systems Bioinformatics Conference , pp. 504-505
    • Chen, X.1
  • 3
    • 0344235442 scopus 로고    scopus 로고
    • Feature selection for support vector machines by means of genetic algorithm
    • Frohlich, H., et al.: Feature Selection for Support Vector Machines by Means of Genetic Algorithm, Tools with Artificial Intelligence. (2003) 142-148.
    • (2003) Tools with Artificial Intelligence , pp. 142-148
    • Frohlich, H.1
  • 4
    • 84958740656 scopus 로고    scopus 로고
    • Anomaly detection enhanced classification in computer intrusion detection
    • Springer-Verlag, Berlin Heidelberg New York
    • Fugate, M., et al.: Anomaly Detection Enhanced Classification in Computer Intrusion Detection. Lecture Notes in Computer Science, Vol. 2388. Springer-Verlag, Berlin Heidelberg New York (2002) 186-197
    • (2002) Lecture Notes in Computer Science , vol.2388 , pp. 186-197
    • Fugate, M.1
  • 5
    • 24944563451 scopus 로고    scopus 로고
    • Robust support vector machines for anomaly detection in computer security
    • CSREA Press
    • Hu, W., et al.: Robust Support Vector Machines for Anomaly Detection in Computer Security. Proc. of Int. Conf. on Machine Learning and Applications 2003, CSREA Press (2003) 168-174
    • (2003) Proc. of Int. Conf. on Machine Learning and Applications 2003 , pp. 168-174
    • Hu, W.1
  • 7
    • 0141723181 scopus 로고    scopus 로고
    • KDD Cup 1999 Data.: http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
    • KDD Cup 1999 Data
  • 8
    • 24944586818 scopus 로고    scopus 로고
    • Network-based intrusion detection with support vector machines
    • Springer-Verlag, Berlin Heidelberg New York
    • Kim, D.S., Park, J.S.: Network-based Intrusion Detection with Support Vector Machines. Lecture Notes in Computer Science, Vol. 2662. Springer-Verlag, Berlin Heidelberg New York (2003) 747-756
    • (2003) Lecture Notes in Computer Science , vol.2662 , pp. 747-756
    • Kim, D.S.1    Park, J.S.2
  • 11
    • 0036085392 scopus 로고    scopus 로고
    • Intrusion detection using neural networks and support vector machines
    • Mukkamala, S., et al.: Intrusion Detection Using Neural Networks and Support Vector Machines. Proc. of IEEE Int. Joint Conf. on Neural Networks (2002) 1702-1707
    • (2002) Proc. of IEEE Int. Joint Conf. on Neural Networks , pp. 1702-1707
    • Mukkamala, S.1
  • 13
    • 24944435114 scopus 로고    scopus 로고
    • Determining optimal decision model for support vector machine by genetic algorithm
    • Springer-Verlag, Berlin Heidelberg New York
    • Ohn, S.-Y., et al.: Determining Optimal Decision Model for Support Vector Machine by Genetic Algorithm. Lecture Notes in Computer Science, Vol. 3314. Springer-Verlag, Berlin Heidelberg New York (2004) 895-902
    • (2004) Lecture Notes in Computer Science , vol.3314 , pp. 895-902
    • Ohn, S.-Y.1
  • 14
    • 24944580423 scopus 로고    scopus 로고
    • Using support vector machine to detect the host-based intrusion IRC
    • Park, J.S., et al: Using Support Vector Machine to Detect the Host-based Intrusion IRC Int. Conf. on Internet Information Retrieval (2002) 172-178
    • (2002) Int. Conf. on Internet Information Retrieval , pp. 172-178
    • Park, J.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.