Research On Intrusion Detection Based On Artificial Immune Theory

Intrusion detection is very important in the defense-in-depth network security framework and a hot topic in computer network security in recent years.Biological immune system prevents the organism from being affected by alien maleficent cells, such as viruses and cells etc. The effect on the inner part of the organism has great resemblance with the security system in the computer field. From the viewpoint of information, biological immune system in fact is a compelling example of massively-parallel information-processing system. It is distributed, adaptive, robust that most computer security system today lack.This paper analyzes various intrusion detection techniques simply and begins with the analyzing of biological immune system, based on which builds an artificial immune system referring to computer security. Artificial immune system which model the principle of imperfect detection, negative selection memory and so on has the powerful ability of information-processing. This paper based on pushdown automata model and Hidden Markov models(HMM), and brings forward the essential method and idea about training and recognition of immune detectors, it has stronger detect Ability than Finite-state automata model, The experiments show this method is effective and efficient, it can recognize the unknown intrusion and memorize the past intrusion. It improved the efficiency of detection. At, a new IDS structure based on HMM and PDA is designed according to Common Intrusion Detection Framework(CIDF).