International Journal of Soft Computing
ISSN: OnlineISSN: Print 1816-9503
Abstract
An Anomaly based Intrusion Detection System is a one which monitors the system or network traffic looking for anomalous behaviour rather than matching the user behaviour pattern alone. Hence, the Anomaly Based Intrusion Detection algorithms have the capability to extend their detection mechanisms to detect unknown attacks. In this research, a Self Learning algorithm for anomaly based Intrusion Detection Model which is based on genetic neural network is proposed. The genetic neural network combines the good global searching ability of Genetic algorithm with the accurate local searching feature of back propagation neural networks. Here, it is used to optimize the initial weights of the neural network. The scope of the algorithm in this proposed research remains in identifying the malicious packet.
How to cite this article:
M. Ravichandran and C.S. Ravichandran. A Self Learning Algorithm for Anomaly Based Intrusion Detection System using Genetic Neural Network.
DOI: https://doi.org/10.36478/ijscomp.2014.117.121
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2014.117.121