DocumentCode :
3638166
Title :
Fast intrusion detection system based on Flexible Neural Tree
Author :
Tomáš Novosád;Jan Platoš;Václav Snášel;Ajith Abraham
Author_Institution :
Department of Computer Science, VŠ
fYear :
2010
Firstpage :
106
Lastpage :
111
Abstract :
Computer security is very important in these days. Computers are used probably in any industry and their protection against attacks is very important task. The protection usually consist in several levels. The first level is preventions. Intrusion detection system (IDS) may be used as next level. IDS is useful in detection of intrusions, but also in monitoring of security issues and the traffic. This paper present IDS based on Flexible Neural Trees. Flexible neural tree is hierarchical neural network, which is automatically created using evolutionary algorithms to solving of defined problem. This is very important, because it is not necessary to set the structure and the weights of neural networks prior the problem is solved. The accuracy of proposed technique is always above 98% and the speed of decision making process enable its using in real-time applications.
Keywords :
"Intrusion detection","Optimization","Input variables","Probes","Testing","Artificial neural networks"
Publisher :
ieee
Conference_Titel :
Information Assurance and Security (IAS), 2010 Sixth International Conference on
Print_ISBN :
978-1-4244-7407-3
Type :
conf
DOI :
10.1109/ISIAS.2010.5604057
Filename :
5604057
Link To Document :
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