Intrusion Detection Based on Fuzzy Neural Networks

Abstract

A new network intrusion detection system is presented in this paper. The system is skillfully combined with fuzzy technique and neural network which architecture and arithmetic is redesigned. In order to overcome the difficulty of specifying the membership function of rules depending on experiences of experts in multi-dimensional space, fuzzy neural network model is introduced to carry through proper nonlinear division of input/output characteristics of complex system and to generate fuzzy rule sets and added membership relation automatically. The new system architecture adopts the network processor to collect and analyze the data in the low layer of network, and a prototype system is established. This prototype system behaves better ability of intrusion detection and lower rate of distort, and that it has the ability to detect unknown attack.