期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2012
卷号：1
期号：2
页码：230
出版社：S&S Publications
摘要：Recent internet based communication technology has an important part in our life. Cyber based communication andnetworks connections are very huge not just in the terms of size, but also in the terms of changing the services offered and themobility of users that make them more vulnerable to various kinds of complex attacks. Security is the main issue of networking, asmalicious 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 notcorrectly classify the malicious activity. In this paper, we have used machine learning approaches based on K-mean clustering andNaive 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.
