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Data · dataset · 2023

CMU-SynTraffic-2023-ImageDataset

Listed in Teesside University Research Data Repository

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).

Description

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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Where it is published

Catalogue records · 1

Topics

Inferred from text
Image 75% · Tabular 75%
Provenance · 1 source records, 11 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/t5p2v7h3vg.215 h agoJSON v1
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concepts[field].anzsrc:field:461103mapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Deep Learning']
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concepts[modality].local:modality:imageenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
concepts[modality].local:modality:tabularenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
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