An Applied Research On Intrusion Detection System Based On Immune Agent In Campus Network

Campus net is now widely set up in colleges in China due to the increasing development of network and communication technology, heavy investment of education resources and the main trend of campus digitalization construction in particular. Nevertheless, campus digitalization construction is confronted with a wide variety of problems at present, among which the security problem cannot be neglected.Intrusion detection system (IDS) is a kind of active network security protection system, which can effectively make up the deficiency of traditional security techniques. Despite the great progress in IDS, there still exist some defects in the traditional IDS. As a result, new techniques that can improve the overall performance of the IDS need to be developed to deal with such problems as high false positive rate, high negative positive rate and speed bottleneck.Intrusion detection technology based on biological immune can detect the intrusion and make reaction, and can construct an artificial immune network system with simulated biological characteristics of distribution, diversity, self-adaptation, automatic response and self-repair. In this case, the artifical immune network system is capable of detecting abnormal phenomena and conducting detection in case of incomplete information as well.Following the analysis of the current security problems of campus network, this paper puts forward the model of intrusion detection based on immune agent by combining immune principles with agent technologies. To be more specific, detection module, communication module and reaction module are carefully designed in this model to anlyze the match rules. In addition, a kind of improved dynamic clonal selection algorithm is proposed to form a detector by analyzing both negative selection algorithm and dynamic clonal selection algorithm. In the end, this paper proves to the readers by experiment that this algorithm is effective and is able to meet the requirements of intrusion detection in campus network.