Research On Intrusion Detection Technology Based On Artificial Immune Principle

Intrusion Detection is the most important aspects in the current network security research field.Biological immune system is a complicated adaptive system,which can effectively differentiate the self proteid and the pathogenic organism,then,clean out the virus.From the informatic aspect,this mechanism contain a wonderful information process ,which brings inspirations to the researchers,and ,people can build intrusion detection model based on biological principle.Currently,this research field is becoming more and more memarkable.Base on the mechanism of the process of the antibody maturation ,we proposed some new algorithms to produce the unmature detector ,such as fitness variation and gene recomposition .at the same time ,we bind the genenic algorithm and the negative seletion algorithm to reproduce the mature detector.The results of Experimental on the KDDcup99 show that the method we proposed is effective.The major works of this dissertation are summarized as fellow:1. The biological immune mechanisms of immune recognition, immune memory and immune response are discussed.Then,we analyzed the coding mode and the corresponding operation . some artificial immune algorithms and the detecton model are analyzed also.2. Genetic negetive selection algorithm is put forward.Base on the dynamic thickness adjusting in dectecor set , genetic negetive selection algorithm can maintain the balance between population convergence and individual diversity,and presents much better performance.3. An intrusion detection system based on this artificial immune model to inspect the network data packet is established and the results of emulational experiments are given.These results prove that the model and corresponding algorithms are effective.