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IJCNN
2000
IEEE

Applying CMAC-Based On-Line Learning to Intrusion Detection

9 years 8 months ago
Applying CMAC-Based On-Line Learning to Intrusion Detection
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 by a modified reinforcement learning method that uses feedback from the protected system.
James Cannady
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where IJCNN
Authors James Cannady
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