Coordinator:
Fabio MARTINELLI
Research Director, CNR

AT 1’s main goal is to investigate how to create a reliable and secure cyberspace by combining robust technological systems with appropriate human behaviour. This will be based on an innovative ecosystem in which experts in technology, law, ethics, sociology and education will join forces to develop a process to define and test new cybersecurity policies using a holistic approach. In particular, WP1 will improve the knowledge on the regulatory, legal and ethical aspects of cyberspace. The detailed objectives of AT 1 can be divided into five broad categories. The first category focuses on the rights, rules, definitions, taxonomies and authorities needed to create new forms of co-regulation in cyberspace. The second category covers the legal and ethical questions in cybersecurity, such as the fundamental rights in the new ecosystem. The third category deals with continuous learning and educational programmes on legal aspects of cybersecurity. The fourth category explores cybercrime and cyber diplomacy as key elements of a new national strategy and aims at raising awareness of this issue among the general public, not just in the academic environment. The fifth category focuses on digital sovereignty, also in relation to computing and technologies based on artificial intelligence, cloud, fog and edge computing, and their applications in specific fields, such as energy and transport.

Project: Law and regulation for a better-safe Cyberspace (CYBERIGHTS)
PI: Andrea SIMONCINI, Full Professor, UNIFI

Project: Digital Sovereignty (DiSe)
PI: Fabio MARTINELLI, Research Director, CNR

  • Gianpiero Costantino, Marco De Vincenzi, Fabio Martinelli, Ilaria Matteucci (2023). Electric Vehicle Security and Privacy: A Comparative Analysis of Charging Methods. VTC2023-Spring 2023: 1-7
  • Francesco Mercaldo, Giovanni Ciaramella, Antonella Santone, Fabio Martinelli (2023). Obfuscated Mobile Malware Detection by Means of Dynamic Analysis and Explainable Deep Learning. ARES 2023: 79:1-79:10
  • Marco De Vincenzi, Ilaria Matteucci, Fabio Martinelli, Stefano Sebastio (2023). Application of Secure Two-Party Computation in a Privacy-Preserving Android App. ARES 2023: 144:1-144:7
  • Fabio Martinelli, Francesco Mercaldo, Antonella Santone (2023). Water Meter Reading for Smart Grid Monitoring. Sensors 23(1): 75 (2023)
  • Elisa Sorrentino, Anna Federica Spagnuolo (2024). Cybersecurity and Digital Sovereignty in the Health Data Protection, submitted in: Rivista italiana di informatica e diritto. 2024.
  • Elena Cardillo, Alessio Portaro, Maria Taverniti, Claudia Lanza, Raffaele Guarasci (2024). Towards the automated population of Thesauri using BERT: a use case on the Cybersecurity domain, The 12-th International Conference on Emerging Internet, Data and Web Technologies (EIDWT-2024) in Advances in Internet, Data & Web Technologies: The 12th International Conference on Emerging Internet, Data & Web Technologies (EIDWT-2024). Springer Cham 2024
  • Francesco Folino, Gianluigi Folino, Francesco Sergio Pisani, Pietro Sabatino, Luigi Pontieri (2024). A Scalable Vertical Federated Learning Framework for Analytics in the Cybersecurity Domain, PDP 2024, The 32nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2024), 20-22 March 2024, Dublin, Ireland.
  • Gianluigi Folino, Agostino Forestiero, Giuseppe Papuzzo (2024) “Self-sovereign identification of IoT Devices by using Physically Unclonable Functions and Blockchain”, selected paper NUMTA 2023 conference, Springer LNCS proceedings, to appear, 2024.
  • F Folino, G Folino, M Guarascio, L Pontieri (2024). Data-& compute-efficient deviance mining via active learning and fast ensembles, Springer, Journal of Intelligent Information Systems, 1-25, 2024.
  • Lonetti, F., Bertolino, A., & Di Giandomenico, F. (2023). Model-based security testing in iot systems: A rapid review. Information and Software Technology, 164, 107326. doi:https://doi.org/10.1016/j.infsof.2023.107326
  • Michela Fazzolari, Pietro Ducange, Francesco Marcelloni (2023). An Explainable Intrusion Detection System for IoT Networks. FUZZ 2023: 1-6
  • Tauheed Waheed, Eda Marchetti (2023). The Impact of IOT Cybersecurity Testing in the Perspective of Industry 5.0. WEBIST 2023: 480-487
  • Said Daoudagh, Eda Marchetti (2023). Breakthroughs in Testing and Certification in Cybersecurity: Research Gaps and Open Problems. ITASEC 2023
  • Said Daoudagh, Eda Marchetti, Antonello Calabrò, Filipa Ferrada, Ana-Inês Oliveira, José Barata, Ricardo Silva Peres, Francisco Marques (2023). DAEMON: A Domain-Based Monitoring Ontology for IoT Systems. SN Comput. Sci. 4(5): 632 (2023)
  • Flavio Lombardi and Alessandro Recchia (2023). On Abstract Machines Security and Performance. In: Procedia Computer Science 231 (2024). 14th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2023), pp. 111–118. issn: 1877-0509. doi: https://doi.org/10.1016/j.procs.2023.12.182.
  • Giovanni Ciaramella, Giacomo Iadarola, Fabio Martinelli, Francesco Mercaldo, Antonella Santone (2023). Explainable Ransomware Detection with Deep Learning Techniques, Journal of Computer Virology and Hacking Techniques, 2023
  • Fabio Martinelli, Francesco Mercaldo, Antonella Santone (2023). A Driver Detection Method by means of Explainable Deep Learning, IEEE International Conference on Cyber Security and Resilience, 2023
  • Mario Cesarelli, Giacomo Iadarola, Fabio Martinelli, Francesco Mercaldo, Antonella Santone (2023). Explainable Deep Learning for Face Mask Detection, 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2023)
  • Amine Hattak, Giacomo Iadarola, Fabio Martinelli, Francesco Mercaldo, Antonella Santone (2023). A Method for Robust and Explainable Image-based Network Traffic Classification with Deep Learning, International Conference on Security and Cryptography (SECRYPT), 2023
  • Giovanni Ciaramella, Giacomo Iadarola, Francesco Mercaldo, Marco Storto, Antonella Santone, Fabio Martinelli (2022). Introducing Quantum Computing in Mobile Malware Detection. ARES 2022