Title :
A new model of intelligent hybrid network intrusion detection system
Author_Institution :
Dept. of Comput. Sci. & Technol., Dezhou Univ., Dezhou, China
Abstract :
Intrusion detection is a dynamic security protection technology that can detect the internal and external network attacks. Now the shortcomings of the single detection system are that the false alarm rate and omission rate is relatively high and detection efficiency is relatively low. In this paper, a new type of intelligent hybrid detection system model is proposed after the comprehensive analysis of the advantages and disadvantages of each system, and we introduced several key module design and algorithm implementation. The model can be flexibly extended to meet different network environment, improve their detection performance and accuracy.
Keywords :
computer network security; neural nets; dynamic security protection technology; false alarm rate; intelligent hybrid network intrusion detection system; neural networks; omission rate; Algorithm design and analysis; Biological neural networks; Computer networks; Computer security; Immune system; Information security; Intelligent networks; Intrusion detection; Neural networks; Pathology; Adaptive genetic algorithm; Immunoassay System; Three-layer BP network;
Conference_Titel :
Bioinformatics and Biomedical Technology (ICBBT), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6775-4
DOI :
10.1109/ICBBT.2010.5478935
