Giampaolo Bovenzi

Orcid: 0000-0002-0997-9724

According to our database¹, Giampaolo Bovenzi authored at least 23 papers between 2019 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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Bibliography

2025

Mapping the Landscape of Generative AI in Network Monitoring and Management.

[BibT_eX]

[DOI]

CoRR, February, 2025

Adaptable, incremental, and explainable network intrusion detection systems for internet of things.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2025

2024

Benchmarking Class Incremental Learning in Deep Learning Traffic Classification.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Serv. Manag., February, 2024

Classifying attack traffic in IoT environments via few-shot learning.

[BibT_eX]

[DOI]

J. Inf. Secur. Appl., 2024

MEMENTO: A novel approach for class incremental learning of encrypted traffic.

[BibT_eX]

[DOI]

Comput. Networks, 2024

An MLOps Framework for Explainable Network Intrusion Detection with MLflow.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Computers and Communications, 2024

2023

Blockchain Performance in Industry 4.0: Drivers, use cases, and future directions.

[BibT_eX]

[DOI]

J. Ind. Inf. Integr., December, 2023

Network anomaly detection methods in IoT environments via deep learning: A Fair comparison of performance and robustness.

[BibT_eX]

[DOI]

Comput. Secur., May, 2023

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

[BibT_eX]

[DOI]

Proceedings of the 35th International Teletraffic Congress, 2023

Few Shot Learning Approaches for Classifying Rare Mobile-App Encrypted Traffic Samples.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2023, 2023

IoT Botnet-Traffic Classification Using Few-Shot Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2023

Adaptive Intrusion Detection Systems: Class Incremental Learning for IoT Emerging Threats.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Hierarchical Classification of Android Malware Traffic.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Trust, 2022

On the use of Machine Learning Approaches for the Early Classification in Network Intrusion Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Measurements & Networking, 2022

A Comparison of Machine and Deep Learning Models for Detection and Classification of Android Malware Traffic.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Computers and Communications, 2022

Data Poisoning Attacks against Autoencoder-based Anomaly Detection Models: a Robustness Analysis.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2022

2021

Characterization and Prediction of Mobile-App Traffic Using Markov Modeling.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Serv. Manag., 2021

Packet-level prediction of mobile-app traffic using multitask Deep Learning.

[BibT_eX]

[DOI]

Comput. Networks, 2021

A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification.

[BibT_eX]

[DOI]

Proceedings of the 5th Network Traffic Measurement and Analysis Conference, 2021

2020

A Dive into the Dark Web: Hierarchical Traffic Classification of Anonymity Tools.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2020

A Big Data-Enabled Hierarchical Framework for Traffic Classification.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2020

A Hierarchical Hybrid Intrusion Detection Approach in IoT Scenarios.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2020

2019

Skin Lesions Classification: A Radiomics Approach with Deep CNN.

[BibT_eX]

[DOI]

Proceedings of the New Trends in Image Analysis and Processing - ICIAP 2019, 2019

Giampaolo Bovenzi

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