Toward Generative Data Augmentation for Traffic Classification

Chao Wang, Alessandro Finamore, Pietro Michiardi, Massimo Gallo, Dario Rossi
10/21/2023
cs.LG

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Abstract

Data Augmentation (DA)-augmenting training data with synthetic samples-is wildly adopted in Computer Vision (CV) to improve models performance. Conversely, DA has not been yet popularized in networking use cases, including Traffic Classification (TC). In this work, we present a preliminary study of 14 hand-crafted DAs applied on the MIRAGE19 dataset. Our results (i) show that DA can reap benefits previously unexplored in TC and (ii) foster a research agenda on the use of generative models to automate DA design.

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Cite this paper

@article{wang2023toward,
  title  = {Toward Generative Data Augmentation for Traffic Classification},
  author = {Chao Wang and Alessandro Finamore and Pietro Michiardi and Massimo Gallo and Dario Rossi},
  year   = {2023},
  eprint = {2310.13935},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.13935v1}
}

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