Abstract
In this paper, we propose a new intrusion detection system: MMIDS (Multi-step Multi-class Intrusion Detection System), which alleviates some drawbacks associated with misuse detection and anomaly detection. The MMIDS consists of a hierarchical structure of one-class SVM, novel multi-class SVM, and incremental clustering algorithm: Fuzzy-ART. It is able to detect novel attacks, to give detail informations of attack types, to provide economic system maintenance, and to provide incremental update and extension with a system.
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Lee, H., Song, J., Park, D. (2005). Intrusion Detection System Based on Multi-class SVM. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_54
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DOI: https://doi.org/10.1007/11548706_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28660-8
Online ISBN: 978-3-540-31824-8
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