With the advancement of digital age and internet technologies cyber-attacks increasingly have been prompting the news headlines. These attacks exploit a network's short comings to gain unauthorized access to the sensitive information or sometimes just create a flood to prevent legitimate users from accessing it. In any case intrusion of the network plays a key role before the execution of any attack. In this paper we will discuss a how these intrusions can be detected with k-means clustering based machine learning approach using big data analytical techniques and put forward the experimental results to prevent attacks at it's very core.
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Kumari et al. (2016) studied this question.
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