DocumentCode :
2850603
Title :
Intrusion detection model based on the improved neural network and expert system
Author :
Gong, Xingchao ; Guan, Xin
Author_Institution :
Sch. of Electron. & Inf. Eng., Liaoning Tech. Univ., Huludao, China
fYear :
2012
fDate :
24-27 June 2012
Firstpage :
191
Lastpage :
193
Abstract :
This paper shows a intrusion detection model that combines the BP networks and the expert system aiming at the bad effect of a single detection model .This model uses the improvement the BP neural network, simultaneously through the similar expert solves the actual problem inference mechanism, creat a neural network expert system model. The experiment simulation show that this model has less iteration times, quicker convergence rate?higher detection rate and sufficient availability, at present mainly applied in the mine network security.
Keywords :
backpropagation; convergence; expert systems; inference mechanisms; iterative methods; neural nets; security of data; BP neural network; convergence rate; detection rate; expert system; inference mechanism; intrusion detection model; iteration times; mine network security; Engines; Probes; BP Network; Expert System; Intrusion Detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2363-5
Type :
conf
DOI :
10.1109/EEESym.2012.6258621
Filename :
6258621
Link To Document :
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