An Improved Dynamic Clonal Selection Algorithm Using Network Intrusion Detection

Abstract

An improved Dynamic Clonal Selection Algorithm (IDCSA) is proposed in this paper which is used in distributed network intrusion detection system (NIDS). It aims to improve the detector's ability to recognize both the known and unknown intrusions by using the strategies of establishing rules of expert knowledge, automatic evolution of gene pools, and optimization of detector generation process. The experimental results show that the proposed IDCSA can reduce FP (false positive) and improve TP (true positive), effectively improve the detection performance and adaptability of the system.