Attribute selection using information gain for a fuzzy logic intrusion detection system
Jesús González-Pino, Janica Edmonds, Mauricio Papa · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
In the modern realm of information technology, data mining and fuzzy logic are often used as effective tools in the development of novel intrusion detection systems. This paper describes an intrusion detection system that effectively deploys both techniques and uses the concept of information gain to guide the attribute selection process. The advantage of this approach is that it provides a computationally efficient solution that helps reduce the overhead associated with the data mining process. Experimental results obtained with a prototype system implementation show promising opportunities for improving the overall detection performance of our intrusion detection system.