Research Of Network Intrusion Detection System Based On Immune Principle

Recently,with the rapid development of internet,more and more attacks to the information systems appear and become much harder to resist than before..The attack modes have changed from the traditional local virus attacks to the distributed,high-speed spread network attacks..Because of their shortcomings,existing intrusion detection techniques can not deal with this situation effectively.Therefore,intrusion detection system(IDS) is improved by using the principle of biological immune for reference.After introducing basic knowledge of intrusion detection and immunology,on the basis of researching the basic characteristics of artificial immune,algorithm and model,network intrusion detection system model based on immune principle is designed in this paper,which is to make up some defects in network intrusion detection.It is an abnormal network intrusion detection system with distributed system configuration.The thesis researches the algorithm of creating initialization detector set applying in the process of negative selection for the IDS mode.Through analyzing existing detector generating algorithm,using the result of evolutionary computation for reference,linear detector generating algorithm(used most currently) is improved.By eliminating redundant detector,the efficiency of generating algorithm,based on the linear time complexity,is enhanced,meanwhile,which ensures that improved algorithm can cover nonego space as much as possible.In the thesis,the initialization detector set scale and the failure probability of detector creation algorithm has been tested and the test results indicate that the improved algorithm enhanced the maturity and the reliability contrasting with the former algorithm.