This dataset is a collection of labelled PCAP files, both encrypted and unencrypted, across 10 applications, as well as a pandas dataframe in HDF5 format containing detailed metadata summarizing the connections from those files. It was created to assist the development of machine learning tools that would allow operators to see the traffic categories of both encrypted and unencrypted traffic flows. In particular, features of the network packet traffic timing and size information (both inside of and outside of the VPN) can be leveraged to predict the application category that generated the traffic.
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This is a real-world industrial benchmark dataset from a major medical device manufacturer for the prediction of customer escalations. The dataset contains features derived from IoT (machine log) and enterprise data including labels for escalation from a fleet of thousands of customers of high-end medical devices.
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