Neural Network Techniques for Host Anomaly Intrusion Detection Using Fixed Pattern Transformation

Author:

Cha ByungRae,Park KyungWoo,Seo JaeHyun

Publisher

Springer Berlin Heidelberg

Reference12 articles.

1. Warrender, C., Forrest, S., Pearlmutter, B.: Detecting Intrusion Using System Calls: Alternative Data Models (1998)

2. Portnoy, L.: Intrusion detection with unlabeled data using clustering, Undergraduate Thesis, Columbia University (2000)

3. Marin, J., Ragsdale, D., Shurdu, J.: A Hybrid Approach to the Profile Creation and Intrusion Detection. In: Proceedings of DARPA Information Survivability Conference and Exposition. IEEE, Los Alamitos (2001)

4. Ye, N., Li, X.: A Scalable Clustering Technique for Intrusion Signature Recognition. In: Proceedings of 2001 IEEE Workshop on Information Assurance and Security (2001)

5. Lee, W., Stolfo, S.J., Chan, P.K., Eskin, E., Fan, W., Miller, M., Hershkop, S., Zhang, J.: Real Time Data Mining – based Intrusion Detection. IEEE, Los Alamitos (2001)

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