Abstract
The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existing intrusion detection approaches require either manual coding of new attacks in expert systems or the complete retraining of a neural network to improve analysis or learn new attacks. This paper presents a new approach to applying adaptive neural networks to intrusion detection that is capable of autonomously learning new attacks rapidly using feedback from the protected system.
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© 2001 Springer-Verlag Berlin Heidelberg
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Cannady, J., Garcia, R.C. (2001). The Application of Fuzzy ARTMAP in the Detection of Computer Network Attacks. In: Dorffner, G., Bischof, H., Hornik, K. (eds) Artificial Neural Networks — ICANN 2001. ICANN 2001. Lecture Notes in Computer Science, vol 2130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44668-0_32
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DOI: https://doi.org/10.1007/3-540-44668-0_32
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