Journal
IEEE COMPUTER GRAPHICS AND APPLICATIONS
Volume 35, Issue 6, Pages 42-50Publisher
IEEE COMPUTER SOC
DOI: 10.1109/MCG.2015.97
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Funding
- National Natural Science Foundation of China [61402540]
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Entropy-based traffic metrics have received much attention in network traffic anomaly detection, but practical issues still hinder widespread adoption. The visual analytic tool ENTVis provides coherent visual analysis that makes entropy-based traffic features more intuitive and helps users interpret network data and more quickly identify traffic anomalies.
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