Research On Intrusion Detection System Based On Immune Mechanism

The purpose of Artificial Immune System is to extract information processing mechanisms contained in biological immune system, and then to study and design the corresponding models and algorithms, which could be used to solve many kinds of complex problems. Artificial Immune System is a novel intelligent Computing research field after Artificial Neural Network and Evolutionary Computation, and it is an emergent interdisciplinary research field generated by life science and computer science.The basic function of biological immune system is to recognize self and non-self, and then to classify and eliminate non-self. Biological immune system has immune recognition, immune memory, immune regulation, immune tolerance, immune surveillance and other characteristics. It is a self-adaptive, self-learning, self-organization, parallel and distributed complex system. By deeply researching into the information processing mechanisms within biological immune system, many effective models and algorithms can be designed and established, and it is of great significance to solve many important and complex problems in national economy and social development.Intrusion Detection System is one of the most important parts in network security research work. Since biological immune system is a very effective self-protected system, which effectively recognizes known and unknown antigens, it brings many inspirations for intrusion detection system. Therefore, new intrusion detection mechanism based on biological immune system becomes more and more remarkable, which is an important force to drive current network security research.The purpose of this dissertation is to explore and research into the learning and detecting mechanisms contained in biological immune system, and then to design efficient models and algorithms for intrusion detection system, to establish intrusion detection system based on biological immune system. The learning and detecting models and algorithms based on biological immune mechanisms are designed with consideration of the function and characteristics of biological immune system and using the theoretical research results of immunology for references, while modeling and analyzing the self-protected function from different levels, emphasizing designing models and algorithms from many aspects of biological immune mechanisms.By extracting the rich information processing mechanisms of biological immune system, this dissertation proposes clonal selection algorithm, detectors adaptively generating algorithms, designed and established the corresponding model and system based on artificial immune systems. The work is not only very important to design novel intrusion detection mechanism, but also very significant to drive the related inter disciplines.