Research On NIDS Based On Immunological Principle

Biological immune system is a complex system of self adaptive, self-learning, self-organization, parallel processing and distributed coordination. The research purpose of Artificial Immune System is to extract special information processing mechanisms contained in biological immune system, and then to study and design the corresponding models and algorithms that could be used to solve many kinds of complex problems. In recent years, immune-based intrusion detection has become a key research area in intrusion detection system, exploring natural immunological theories, mechanisms and principles for detecting and reacting to intrusions.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 the characteristics of immune recognition, immune memory, immune regulation, immune tolerance, immune surveillance etc. By deeply researching into various information processing mechanisms contained in biological immune system, many effective models of intrusion detection and algorithms can be established and designed, and it is of great significance to the establishment of new theory and new method of intrusion detection based on biological immune system, also to the change of the current situation of network security.The purpose of this paper is to explore and research into the learning and detecting mechanisms contained in biological immune system, and then to use the technology of artificial immune, to design efficient models and algorithms for intrusion detection system. The main research work of this paper can be summarized as follows:Firstly, on the basis of discussing the creation and updating of the detector the paper makes some improvement on existing artificial immune algorithms. The modification includes co-simulation, mutation of detector, redundancy avoided and evolution of detector, making the artificial immune model reasonable.Secondly, the paper introduces inheritance mechanism and reselection mechanism into clonal selection algorithm, comes up with an improved clonal selection algorithm used for evolving detector, creates memory detector with higher efficiency of detection, and then the experimentation proves the advantage of the algorithm. Afterwards, the paper introduces mutation mechanism and redundancy avoided mechanism into dynamic clonal selection algorithm, comes up with an improved dynamic clonal selection algorithm used for detecting intrusion, and then the experimentation proves the efficiency of the algorithm.Finally, the two algorithms discussed above the paper come up with a distributed network intrusion detection system with higher efficiency of detection.