Toward Generative Data Augmentation for Traffic Classification

• URL: http://arxiv.org/abs/2310.13935v1
• Date: Sat, 21 Oct 2023 08:08:37 GMT
• Title: Toward Generative Data Augmentation for Traffic Classification
• Authors: Chao Wang, Alessandro Finamore, Pietro Michiardi, Massimo Gallo, Dario Rossi
• Abstract summary: Data Augmentation (DA)-augmenting training data with synthetic samples-is wildly adopted in Computer Vision (CV) to improve models performance. DA has not been yet popularized in networking use cases, including Traffic Classification (TC)
• Score: 54.92823760790628
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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