Anomaly Detection in Network Traffic using K-mean clustering

被引:0
|
作者
Kumari, R. [1 ]
Sheetanshu [1 ]
Singh, M. K. [2 ]
Jha, R. [1 ]
Singh, N. K. [1 ]
机构
[1] BIT Mesra, Dept Comp Sci & Engn, Ranchi, Bihar, India
[2] Ranchi Univ, Dept Math, Ranchi 834008, Bihar, India
来源
2016 3RD INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN INFORMATION TECHNOLOGY (RAIT) | 2016年
关键词
Anomaly detection; network intrusion; Big data; k-mean; Spark;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:372 / 378
页数:7
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