Abstrait

An Efficient Classification Mechanism Using Machine Learning Techniques For Attack Detection From Large Dataset

Vineet Richhariya,Dr. J.L.Rana,Dr. R.K.Pandey,Dr. R.C.Jain

Recent internet based communication technology has an important part in our life. Cyber based communication and networks connections are very huge not just in the terms of size, but also in the terms of changing the services offered and the mobility of users that make them more vulnerable to various kinds of complex attacks. Security is the main issue of networking, as malicious activities perform in the network by inside and outside users. There are number of intrusions present in the network. There are number of strategy, which have been developed in order to detect malicious activities. But a single algorithm does not correctly classify the malicious activity. In this paper, we have used machine learning approaches based on K-mean clustering and Naive Bayesian, to efficiently detect the intrusions present in the network. These algorithms have resulted in improved Precision, and reduce the false positive rate in order to provide better performance as compared to some exiting research works