An Efficient Framework for Intrusion Detection in Heterogeneous Network Using Intrusion Pattern Recognition Methods

Abstract

An Intrusion Detection System is a challenging and rapidly growing research field nowadays over the network. There is a possibility of increased development of intrusion or security issues occur in future. Some Systems are limited in identification and recognition of the intrusion and to enhance the victims such as a virus scanner or a firewall rule. Several well-known illustrations of attacks are portraying that they propagate at very high speeds on the internet. Thus there is a need to construct a Generic model to inspect the incoming packets over the internet. This work focuses on modeling an intelligent system for efficient detection of intrusion. The integrated system of header information and payload inspection increases the prediction rate of the intrusion detection and recognition, but it provides less performance rate while integration. Thus the approach of identifying and recognizing the attacks in the network traffic by using a novel framework known to be Intelligent Intrusion Detection Framework (IIDF) is employed to detect, recognize and label the intrusion suspected packet header and payload to increase the performance as well as the prediction rate of the inspection. newline