Evaluating Neural Network Intrusion Detection Approaches Using Analytic Hierarchy Process

• Main Authors: Ahmad, iftikhar, Azween, Abdullah
• Format: Conference or Workshop Item
• Published: 2010
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utp.edu.my/2255/1/Evaluating_Neural_Network_Intrusion_Detection.pdf; http://eprints.utp.edu.my/2255/
• Institution: Universiti Teknologi Petronas

At present age, security in computer and network systems is a pressing concern because a solo attack may cause an immense destruction in computer and network systems. Various intrusion detection approaches be present to resolve this serious issue but the dilemma is which one is more appropriate in the field of intrusion. Therefore, in this paper, we evaluated and compared different neural network (NN) approaches to intrusion detection. This work describes the concepts, tool and methodology being used for assay of different NN intrusion detection approaches using Analytic Hierarchy Process (AHP). Further, conclusion on results is made and direction for future works is presented. The outcome of this work may help and guide the security implementers in two possible ways, either by using the results directly obtained in this paper or by extracting the results using similar mechanism but on different intrusion detection systems or approaches.