Research On Intrusion Detection System Based On Biological Immune Principle

Nowadays, with the rapid development of the network technology, current situation of network security is becoming more and more worrying. All kinds of technology of network security are ceaselessly developed with the appearance of the importance of network security. Intrusion detection system has so similar function with immune systems that it could provide a naive template for Research and Development network intrusion detection system. The goal of this research is to solve network intrusion detection system problem using immune principles and algorithm extracted from immune system. The primary contributions of this dissertation are as follows:The resemblance of the construction from the analogy of the mapping relations between artificial immune system and network intrusion detection system, put forward the possibility and the necessity of network intrusion detection system model based on artificial immune system. Getting the spirit from principle of B-Cell and T-Cell in the biological immune system, this paper proposes a co-evolutionary method with B-Cell and T-Cell in artificial immune system.It also describes how the B-Cell and T-Cell detect antigens cooperatively and how the B-Cell and T-Cell evolve.Research of a network intrusion detection model based immune principles. Firstly, describe the problem of intrusion detection strictly. Secondly, research the new intrusion detection model based the immune principles that this paper proposes, primary analysis the architectural framework and the work principles and the primary features and problem of this model. Finally, fulfill the model by C++ language. Validation of usability and creativeness of the model. Firstly, put forward the aim of test. Secondly, build the needed datasets of simulate test. Through the simulate test and the result analysis, validate the usability and creativeness of the model.Lastly, the dissertation summarizes all the research work mentioned above and discusses the next task in this field.