Survey anomaly detection in network using big data analytics

Y.S. Kalai Vani, Krishnamurthy
<span title="">2017</span> <i title="IEEE"> 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) </i> &nbsp;
Analysing network flows, logs, and system events has been used for intrusion detection. Network flows, logs, and system events, etc. generate big data. Big Data analytics can correlate multiple information sources into a coherent view, identify anomalies and suspicious activities, and finally achieve effective and efficient intrusion detection. This paper presents methods and subsequent evaluation criteria for network intrusion detection, stream data characteristics and stream processing
more &raquo; ... , feature extraction and data reduction, conventional data mining and machine learning, deep learning, and Big Data analytics in network intrusion detection. Current challenges of these methods in intrusion detection are also introduced.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/icecds.2017.8390083</a> <a target="_blank" rel="external noopener" href="">fatcat:6gij7behqjhezefwcxoflowtqe</a> </span>
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