Fuzzy particle swarm optimization for intrusion detection

Abstract

This paper tries to propose a fuzzy particle optimization algorithm (FPSO) for intrusion detection. The proposed FPSO classifier works on a knowledge base modelled as a fuzzy rule if-then and improved by a PSO algorithm. The objective is to obtain good quality solutions by optimizing the fuzzy rules generation. The method is tested on the benchmark KDD'99 intrusion dataset and compared with the fuzzy genetic algorithm and with other existing techniques available in the literature. The obtained results show the efficiency of the proposed approach. © 2012 Springer-Verlag.