Application of decision rules classifier in network intrusion detection
Baohua Zhang · Computer Engineering and Applications Journal · 2012
As a kind of active defense technology,intrusion detection system makes up for the shortcomings of traditional security technology.In addition,it also has real-time monitoring function,greatly improves the safety of computer network system.This paper presents a decision rules binary classifier applied for network intrusion detection.The classifier is optimized by a multiobjective evolutionary algorithm in order to maximize both the classification accuracy and the coverage level.The coverage level is the percentage of items that are classified,in opposite to items unable to be classified.Study results provide very good accuracy and coverage level in detecting attacks.