Immune Mobile Agent and Its Application in Intrusion Detection System

In current distributed intrusion detection systems, the data is collected mostly using distributed component to collect data sent for processing center. Data is analyzed in the processing center. Nevertheless, these models have the following problems: bad real time capability, bottleneck, and single point of failure. In addition, because of the low detecting speed and high false positive rate of traditional intrusion detection system. In order to overcome these shortcomings of current intrusion detection techniques, we have constructed an immune agent by combining immune system with mobile agent. a new distributed intrusion detection model based on mobile agent is proposed in this paper. Intelligent and mobile characteristics of the agent are used to make computing move to data. Analysis shows that the network load can be reduced and the real time capability of the system can be improved with the new model. The system is robust and fault-tolerant. Because mobile agent only can improve the structure of system, dynamic clonal selection algorithm is adopted for reducing false positive rate. The simulation results on KDD99 data set prove that the new model has low false positive rate and high detection rate.

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