Incremental and few-shot learning
Traffic classifiers that learn new apps and classes from few samples, or incrementally, without being retrained from scratch.
Tools & projects
People
Antonio PescapèFull Professor · Principal Investigator
Francesco CerasuoloPostdoc
Alfredo NascitaAssistant Professor (RTDA)
Giuseppe AcetoAssociate Professor
Domenico CiuonzoAssociate Professor
Davide di MondaPostdoc
Antonio MontieriTenure-Track Professor
Valerio PersicoAssociate Professor
Vincenzo SpadariPhD Student
Idio GuarinoAssistant Professor (Non-Tenure Track) - Alma Mater Studiorum University of Bologna
Publications
- Journal R. Carillo, F. Cerasuolo, G. Bovenzi, D. Ciuonzo, A. Pescapè, “A Federated and Incremental Network Intrusion Detection System for IoT Emerging Threats”, IEEE Transactions on Network and Service Management, 2026.
- Journal D. Di Monda, G. Bovenzi, A. Montieri, V. Persico, A. Pescapè, “Analyzing the impact of shifts in encrypted mobile-app traffic on multimodal few-shot learning”, Computer Networks, 2025.
- Conference D. Di Monda, F. Rustam, A. D. Jurcut, A. Pescapè, “Rapid Few-Shot Learning for Resilient Multi-Domain Intrusion Detection”, GLOBECOM 2025 - 2025 IEEE Global Communications Conference, 2025.
- Conference F. Cerasuolo, G. Bovenzi, A. Montieri, A. Pescapè, “Class Incremental Learning for Network-Agnostic Intrusion Detection Systems”, 2025 IEEE 9th Forum on Research and Technologies for Society and Industry (RTSI), 2025.
- Journal R. Carillo, F. Cerasuolo, G. Bovenzi, D. Ciuonzo, A. Pescapè, “Explainable federated class incremental learning for Encrypted Network Traffic classification”, Computer Networks, 2025.
- Journal F. Cerasuolo, G. Bovenzi, D. Ciuonzo, A. Pescapè, “Attack-adaptive network intrusion detection systems for IoT networks through class incremental learning”, Computer Networks, 2025.
- Journal F. Cerasuolo, G. Bovenzi, D. Ciuonzo, A. Pescapè, “Adaptable, incremental, and explainable network intrusion detection systems for internet of things”, Engineering Applications of Artificial Intelligence, 2025.
- Journal F. Cerasuolo, A. Nascita, G. Bovenzi, G. Aceto, D. Ciuonzo, A. Pescapè, D. Rossi, “MEMENTO: A novel approach for class incremental learning of encrypted traffic”, Computer Networks, 2024.
- Conference F. Cerasuolo, G. Bovenzi, V. Spadari, D. Ciuonzo, A. Pescapè, “Explainable Few-Shot Class Incremental Learning for Mobile Network Traffic Classification”, GLOBECOM 2024 - 2024 IEEE Global Communications Conference, 2024.
- Journal G. Bovenzi, D. Di Monda, A. Montieri, V. Persico, A. Pescapè, “Classifying attack traffic in IoT environments via few-shot learning”, Journal of Information Security and Applications, 2024.
- Journal D. Di Monda, A. Montieri, V. Persico, P. Voria, M. De Ieso, A. Pescapè, “Few-Shot Class-Incremental Learning for Network Intrusion Detection Systems”, IEEE Open Journal of the Communications Society, 2024.
- Conference G. Bovenzi, D. Di Monda, A. Montieri, V. Persico, A. Pescapè, “Meta Mimetic: Few-Shot Classification of Mobile-App Encrypted Traffic via Multimodal Meta-Learning”, 2023 35th International Teletraffic Congress (ITC-35), 2023.
- Conference A. Nascita, F. Cerasuolo, G. Aceto, D. Ciuonzo, V. Persico, A. Pescapè, “Explainable Mobile Traffic Classification: the Case of Incremental Learning”, Proceedings of the 2023 on Explainable and Safety Bounded, Fidelitous, Machine Learning for Networking, 2023. PDF
- Conference I. Guarino, C. Wang, A. Finamore, A. Pescapè, D. Rossi, “Many or Few Samples?: Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification”, 2023 7th Network Traffic Measurement and Analysis Conference (TMA), 2023.
- Journal G. Bovenzi, A. Nascita, L. Yang, A. Finamore, G. Aceto, D. Ciuonzo, A. Pescapè, D. Rossi, “Benchmarking Class Incremental Learning in Deep Learning Traffic Classification”, IEEE Transactions on Network and Service Management, 2023.
- Conference G. Bovenzi, D. Di Monda, A. Montieri, V. Persico, A. Pescapè, “Few Shot Learning Approaches for Classifying Rare Mobile-App Encrypted Traffic Samples”, IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2023.
- Conference D. Di Monda, G. Bovenzi, A. Montieri, V. Persico, A. Pescapè, “IoT Botnet-Traffic Classification Using Few-Shot Learning”, 2023 IEEE International Conference on Big Data (BigData), 2023.
- Conference F. Cerasuolo, G. Bovenzi, C. Marescalco, F. Cirillo, D. Ciuonzo, A. Pescapè, “Adaptive Intrusion Detection Systems: Class Incremental Learning for IoT Emerging Threats”, 2023 IEEE International Conference on Big Data (BigData), 2023.
- Preprint G. Bovenzi, L. Yang, A. Finamore, G. Aceto, D. Ciuonzo, A. Pescapè, D. Rossi, “A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification”, arXiv (Cornell University), 2021. PDF