Title :
Research on the Network Intrusion Detection Based on the Immune System
Author :
Lin, Tao ; Sun, He-xu ; Peng, Yu-Qing ; Lei, Zhao-Ming
Author_Institution :
Dept. of Autom., Hebei Univ. of Technol., Tianjin
Abstract :
A network intrusion detection model based on immune system is constructed after a thorough studying for the natural immunological principle. It applied clone recombine, negative selection, and gene evolution and antibody diversity into network intrusion detection. Two detection strategy - misuse and abnormality detection are combined organically, and information plus theory is used to select gene classes. Experiments show accuracy rate of intrusion detection is improved
Keywords :
computer networks; security of data; abnormality detection; antibody diversity; clone recombine; gene classes; gene evolution; immune system; information plus theory; misuse detection; natural immunological principle; negative selection; network intrusion detection; Automation; Chemicals; Cloning; Computer networks; Computer science; Cybernetics; Detectors; Genetic mutations; Immune system; Intrusion detection; Machine learning; Pathogens; Sun; Network intrusion detection; clone recombine; gene evolution; immune system; information plus theory;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.259162
