Francesco Cerasuolo

Orcid: 0009-0000-6476-8092

According to our database1, Francesco Cerasuolo authored at least 18 papers between 2012 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
A Federated and Incremental Network Intrusion Detection System for IoT Emerging Threats.
IEEE Trans. Netw. Serv. Manag., 2026

Cross-network transferability of AI-based network intrusion detection systems in heterogeneous Internet of Things environments.
Comput. Networks, 2026

2025
Mapping the Landscape of Generative AI in Network Monitoring and Management.
IEEE Trans. Netw. Serv. Manag., June, 2025

Adaptable, incremental, and explainable network intrusion detection systems for internet of things.
Eng. Appl. Artif. Intell., 2025

Attack-adaptive network intrusion detection systems for IoT networks through class incremental learning.
Comput. Networks, 2025

Explainable federated class incremental learning for Encrypted Network Traffic classification.
Comput. Networks, 2025

Class Incremental Learning for Network-Agnostic Intrusion Detection Systems.
Proceedings of the 9th IEEE Forum on Research and Technologies for Society and Industry, 2025

Federated Incremental Learning for Encrypted Network Traffic Classification.
Proceedings of the 7th International Conference on Blockchain Computing and Applications, 2025

2024
MEMENTO: A novel approach for class incremental learning of encrypted traffic.
Comput. Networks, 2024

XAI for Interpretable Multimodal Architectures with Contextual Input in Mobile Network Traffic Classification.
Proceedings of the IFIP Networking Conference, 2024

An MLOps Framework for Explainable Network Intrusion Detection with MLflow.
Proceedings of the IEEE Symposium on Computers and Communications, 2024

Explainable Few-Shot Class Incremental Learning for Mobile Network Traffic Classification.
Proceedings of the 2024 IEEE Global Communications Conference, 2024

2023
Explainable Mobile Traffic Classification: the Case of Incremental Learning.
SAFE@CoNEXT, 2023

Adaptive Intrusion Detection Systems: Class Incremental Learning for IoT Emerging Threats.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Prediction of Mobile-App Network-Video-Traffic Aggregates using Multi-task Deep Learning.
Proceedings of the IFIP Networking Conference, 2022

A Comparison of Machine and Deep Learning Models for Detection and Classification of Android Malware Traffic.
Proceedings of the IEEE Symposium on Computers and Communications, 2022

Machine and Deep Learning Approaches for IoT Attack Classification.
Proceedings of the IEEE INFOCOM 2022, 2022

2012
Visualization with a New Visual Metaphor for Hierarchical and Stratified Temporal Domain.
Proceedings of the Web and Wireless Geographical Information Systems, 2012


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