DocumentCode
736892
Title
Intelligent Intrusion Detection Based on Soft Computing
Author
Yan, Chen
fYear
2015
fDate
13-14 June 2015
Firstpage
577
Lastpage
580
Abstract
Aiming at false negative rate and false alart rate which exist generally in the intrusion detection system, a intelligent intrusion detection model is proposed in this paper. Based on the characteristics of global superiority of genetic algorithm and locality of nerve, the model optimizes the weights of the neural network using genetic algorithm. Experiment results show that the intelligent way can improve the efficiency of the intrusion detection.
Keywords
Computational modeling; Computers; Genetic algorithms; Genetics; Intrusion detection; Neural networks; Training; genetic algorithm; intelligent intrusion detection; neural network; soft computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation (ICMTMA), 2015 Seventh International Conference on
Conference_Location
Nanchang, China
Print_ISBN
978-1-4673-7142-1
Type
conf
DOI
10.1109/ICMTMA.2015.145
Filename
7263639
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