Skin Lesions Classification: A Radiomics Approach with Deep CNN. - Gabriele Piantadosi; Giampaolo Bovenzi; Giuseppe Argenziano; Elvira Moscarella; Domenico Parmeggiani; Ludovico Docimo; Carlo Sansone (ICIAP Workshops, 2019)

A Hierarchical Hybrid Intrusion Detection Approach in IoT Scenarios. - Giampaolo Bovenzi; Giuseppe Aceto; Domenico Ciuonzo; Valerio Persico; Antonio Pescapè (GLOBECOM, 2020)

A Big Data-Enabled Hierarchical Framework for Traffic Classification. - Giampaolo Bovenzi; Giuseppe Aceto; Domenico Ciuonzo; Valerio Persico; Antonio Pescapè (IEEE Trans. Netw. Sci. Eng., 2020)

A Dive into the Dark Web: Hierarchical Traffic Classification of Anonymity Tools. - Antonio Montieri; Domenico Ciuonzo; Giampaolo Bovenzi; Valerio Persico; Antonio Pescapè (IEEE Trans. Netw. Sci. Eng., 2020)

A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification. - Giampaolo Bovenzi; Lixuan Yang; Alessandro Finamore; Domenico Ciuonzo; Giuseppe Aceto; Antonio Pescapè; Dario Rossi 001 (TMA, 2021)

Packet-level prediction of mobile-app traffic using multitask Deep Learning. - Antonio Montieri; Giampaolo Bovenzi; Giuseppe Aceto; Domenico Ciuonzo; Valerio Persico; Antonio Pescapè (Comput. Networks, 2021)

Characterization and Prediction of Mobile-App Traffic Using Markov Modeling. - Giuseppe Aceto; Giampaolo Bovenzi; Domenico Ciuonzo; Antonio Montieri; Valerio Persico; Antonio Pescapè (IEEE Trans. Netw. Serv. Manag., 2021)

Data Poisoning Attacks against Autoencoder-based Anomaly Detection Models: a Robustness Analysis. - Giampaolo Bovenzi; Alessio Foggia; Salvatore Santella; Alessandro Testa; Valerio Persico; Antonio Pescapè (ICC, 2022)

A Comparison of Machine and Deep Learning Models for Detection and Classification of Android Malware Traffic. - Giampaolo Bovenzi; Francesco Cerasuolo; Antonio Montieri; Alfredo Nascita; Valerio Persico; Antonio Pescapè (ISCC, 2022)

On the use of Machine Learning Approaches for the Early Classification in Network Intrusion Detection. - Idio Guarino; Giampaolo Bovenzi; Davide Di Monda; Giuseppe Aceto; Domenico Ciuonzo; Antonio Pescapè (M&N, 2022)

Hierarchical Classification of Android Malware Traffic. - Giampaolo Bovenzi; Valerio Persico; Antonio Pescapè; Anna Piscitelli; Vincenzo Spadari (TrustCom, 2022)

A hierarchical learning framework for network traffic analysis: design, implementation, and use cases. - Giampaolo Bovenzi (2022)

Adaptive Intrusion Detection Systems: Class Incremental Learning for IoT Emerging Threats. - Francesco Cerasuolo; Giampaolo Bovenzi; Christian Marescalco; Francesco Cirillo; Domenico Ciuonzo; Antonio Pescapè (IEEE Big Data, 2023)

IoT Botnet-Traffic Classification Using Few-Shot Learning. - Davide Di Monda; Giampaolo Bovenzi; Antonio Montieri; Valerio Persico; Antonio Pescapè (IEEE Big Data, 2023)

Few Shot Learning Approaches for Classifying Rare Mobile-App Encrypted Traffic Samples. - Giampaolo Bovenzi; Davide Di Monda; Antonio Montieri; Valerio Persico; Antonio Pescapè (INFOCOM Workshops, 2023)

Meta Mimetic: Few-Shot Classification of Mobile-App Encrypted Traffic via Multimodal Meta-Learning. - Giampaolo Bovenzi; Davide Di Monda; Antonio Montieri; Valerio Persico; Antonio Pescapè (ITC, 2023)

Network anomaly detection methods in IoT environments via deep learning: A Fair comparison of performance and robustness. - Giampaolo Bovenzi; Giuseppe Aceto; Domenico Ciuonzo; Antonio Montieri; Valerio Persico; Antonio Pescapè (Comput. Secur., 2023)

Blockchain Performance in Industry 4.0: Drivers, use cases, and future directions. - Giampaolo Bovenzi; Giuseppe Aceto; Valerio Persico; Antonio Pescapè (J. Ind. Inf. Integr., 2023)

Explainable Few-Shot Class Incremental Learning for Mobile Network Traffic Classification. - Francesco Cerasuolo; Giampaolo Bovenzi; Vincenzo Spadari; Domenico Ciuonzo; Antonio Pescapè (GLOBECOM, 2024)

An MLOps Framework for Explainable Network Intrusion Detection with MLflow. - Vincenzo Spadari; Francesco Cerasuolo; Giampaolo Bovenzi; Antonio Pescapè (ISCC, 2024)

MEMENTO: A novel approach for class incremental learning of encrypted traffic. - Francesco Cerasuolo; Alfredo Nascita; Giampaolo Bovenzi; Giuseppe Aceto; Domenico Ciuonzo; Antonio Pescapè; Dario Rossi 001 (Comput. Networks, 2024)

Classifying attack traffic in IoT environments via few-shot learning. - Giampaolo Bovenzi; Davide Di Monda; Antonio Montieri; Valerio Persico; Antonio Pescapè (J. Inf. Secur. Appl., 2024)

Benchmarking Class Incremental Learning in Deep Learning Traffic Classification. - Giampaolo Bovenzi; Alfredo Nascita; Lixuan Yang; Alessandro Finamore; Giuseppe Aceto; Domenico Ciuonzo; Antonio Pescapè; Dario Rossi 001 (IEEE Trans. Netw. Serv. Manag., 2024)

Explainable federated class incremental learning for Encrypted Network Traffic classification. - Raffaele Carillo; Francesco Cerasuolo; Giampaolo Bovenzi; Domenico Ciuonzo; Antonio Pescapè (Comput. Networks, 2025)

Attack-adaptive network intrusion detection systems for IoT networks through class incremental learning. - Francesco Cerasuolo; Giampaolo Bovenzi; Domenico Ciuonzo; Antonio Pescapè (Comput. Networks, 2025)

Adaptable, incremental, and explainable network intrusion detection systems for internet of things. - Francesco Cerasuolo; Giampaolo Bovenzi; Domenico Ciuonzo; Antonio Pescapè (Eng. Appl. Artif. Intell., 2025)

Mapping the Landscape of Generative AI in Network Monitoring and Management. - Giampaolo Bovenzi; Francesco Cerasuolo; Domenico Ciuonzo; Davide Di Monda; Idio Guarino; Antonio Montieri; Valerio Persico; Antonio Pescapè (IEEE Trans. Netw. Serv. Manag., 2025)