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UOT 004
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Biblioqrafik təsvir | Aliguliyev , R.M. Classification Ensemble based anomaly detection in network traffic / R.M. Aliguliyev , M.S. Hajirahimova // Review of Computer Engineering Research. - 2019. - N: 6(1). - P. 12-23. | Annotasiya | Recently, the expansion of information technologies and the exponential increase of the
digital data have deepened more the security and confidentiality issues in computer
networks. In the Big Data era information security has become the main direction of
scientific research and Big Data analytics is considered being the main tool in the
solution of information security issue. Anomaly detection is one of the main issues in
data analysis and used widely for detecting network threats. The potential sources of
outliers can be noise and errors, events, and malicious attacks on the network. In this
work, a short review of network anomaly detection methods is given, is looked at
related works. In the article, a more exact and simple multi-classifier model is proposed
for anomaly detection in network traffic based on Big Data. Experiments have been
performed on the NSL-KDD data set by using the Weka. The offered model has shown
decent results in terms of anomaly detection accuracy. | Elektron variant | Elektron variant |
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