Mining Anomalies in Large ISCX Dataset Using Machine Learning Algorithms in KNIME
Proceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2018 held at Malaviya National Institute of Technology, Jaipur (India) on March 26-27, 2018
6 Pages Posted: 9 May 2018
Date Written: April 28, 2018
The growth of Internet has led to birth of new and strong network based attacks. These attacks cannot be completely detected with traditional supervised intrusion detection techniques. Machine Learning based on unsupervised learning is slowly taking it’s place. Moreover the rate of traffic has increased tremendously. It is important to work on tools and techniques that can support large volumes of data. It is under these scenarios that we have worked on KNIME to understand it’s scope in handling big datasets of more than 20 Gbs.
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