16 citations · 16 across the 4 of their papers we have counts for
4 papers
Lightweight GenAI for Network Traffic Generation: Fidelity, Augmentation, and Classification
Giampaolo Bovenzi, Domenico Ciuonzo, Jonatan Krolikowski +4
Network Traffic Classification (NTC) increasingly relies on data-driven models, yet its practical deployment is often constrained by limited labeled data, strict privacy requiremen…
Data Augmentation for Traffic Classification
Chao Wang, Alessandro Finamore, Pietro Michiardi +2
Data Augmentation (DA) -- enriching training data by adding synthetic samples -- is a technique widely adopted in Computer Vision (CV) and Natural Language Processing (NLP) tasks t…
Toward Generative Data Augmentation for Traffic Classification
Chao Wang, Alessandro Finamore, Pietro Michiardi +2
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 popu…
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation
Alessandro Finamore, Chao Wang, Jonatan Krolikowski +3
Over the last years we witnessed a renewed interest toward Traffic Classification (TC) captivated by the rise of Deep Learning (DL). Yet, the vast majority of TC literature lacks c…