On the use of machine learning approaches for the early classification in network intrusion detection I Guarino, G Bovenzi, D Di Monda, G Aceto, D Ciuonzo, A Pescapé 2022 IEEE International symposium on measurements & networking (M&N), 1-6, 2022 | 18 | 2022 |
Contextual counters and multimodal Deep Learning for activity-level traffic classification of mobile communication apps during COVID-19 pandemic I Guarino, G Aceto, D Ciuonzo, A Montieri, V Persico, A Pescapè Computer Networks 219, 109452, 2022 | 14 | 2022 |
Classification of communication and collaboration apps via advanced deep-learning approaches I Guarino, G Aceto, D Ciuonzo, A Montieri, V Persico, A Pescapé 2021 IEEE 26th International Workshop on Computer Aided Modeling and Design …, 2021 | 9 | 2021 |
Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification I Guarino, C Wang, A Finamore, A Pescape, D Rossi arXiv preprint arXiv:2305.12432, 2023 | 6 | 2023 |
Characterizing and modeling traffic of communication and collaboration apps bloomed with COVID-19 outbreak I Guarino, G Aceto, D Ciuonzo, A Montieri, V Persico, A Pescapè 2021 IEEE 6th International Forum on Research and Technology for Society and …, 2021 | 3 | 2021 |
Mobile network traffic prediction using high order Markov chains trained at multiple granularity I Guarino, A Nascita, G Aceto, A Pescapà 2021 IEEE 6th International Forum on Research and Technology for Society and …, 2021 | 2 | 2021 |
Explainable Deep-Learning Approaches for Packet-Level Traffic Prediction of Collaboration and Communication Mobile Apps I Guarino, G Aceto, D Ciuonzo, A Montieri, V Persico, A Pescapè IEEE Open Journal of the Communications Society, 2024 | 1 | 2024 |
Fine-Grained Traffic Prediction of Communication-and-Collaboration Apps via Deep-Learning: a First Look at Explainability I Guarino, G Aceto, D Ciuonzo, A Montieri, V Persico, A Pescapé ICC 2023-IEEE International Conference on Communications, 1609-1615, 2023 | 1 | 2023 |
XAI for Interpretable Multimodal Architectures with Contextual Input in Mobile Network Traffic Classification F Cerasuolo, I Guarino, V Spadari, G Aceto, A Pescapé | | |