CMU-SynTraffic-2023-ImageDataset
Published: 16 February 2023| Version 2 | DOI: 10.17632/t5p2v7h3vg.2
Contributors:
Nathan Briner, , , Description
This dataset contains tabular network traffic data from the CMU-Syntraffic-2022 dataset that has been transformed into images using the following tabular-to-image techniques: Binary Image Encoding, IGTD, DeepInsight, and feature wrapping (normalized and non-normalized). The data selected from CMU-Syntraffic-2022 contains real network traffic data from the CIC-Darknet2020 dataset along with synthetic data generated using SMOTE. This dataset is not intended to be used in its entirety as it contains different representations of identical samples. The intended use for this dataset is for research on CNN based anonymous network traffic classification and testing the viability of tabular-to-image algorithms.
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Categories
Cybersecurity, Machine Learning, Internet Protocol, Virtual Private Network, Deep Learning