Prelimary work on generative data augmentation for traffic classification accepted at Conext SW 2023

Our abstract titled “Toward Generative Data Augmentation for Traffic Classification” will be presented at Conext Student Workshop 2023

Congrats to Chao Wang.

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.