Self-Supervised Traffic Classification: Flow Embedding and Few-Shot Solutions

E Horowicz, T Shapira, Y Shavitt - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Internet traffic classification has been intensively studied over the past decade due to its
importance for traffic engineering and cyber security. A promising approach to several traffic …

[HTML][HTML] Classifying attack traffic in IoT environments via few-shot learning

G Bovenzi, D Di Monda, A Montieri, V Persico… - Journal of Information …, 2024 - Elsevier
Abstract The Internet of Things (IoT) is a key enabler for critical systems, but IoT devices are
increasingly targeted by cyberattacks due to their diffusion and hardware and software …

Meta Mimetic: Few-Shot Classification of Mobile-App Encrypted Traffic via Multimodal Meta-Learning

G Bovenzi, D Di Monda, A Montieri… - … Congress (ITC-35), 2023 - ieeexplore.ieee.org
Despite its proven effectiveness in classifying encrypted network traffic, deep learning
requires large amounts of labeled data to feed typical data-hungry training processes. Few …

IoT Botnet-Traffic Classification Using Few-Shot Learning

D Di Monda, G Bovenzi, A Montieri… - … Conference on Big …, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) is experiencing a constant expansion, embedding connectivity
into everyday objects for increased efficiency. Despite this, security vulnerabilities pose a …