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Roberto Di Pietro

Professor, Computer Science

Computer, Electrical and Mathematical Science and Engineering Division

roberto.dipietro@kaust.edu.sa


Affiliations

Education Profile

  • Post-doc at the National Research Council ('04-'06), Pisa-Italy
  • Ph.D. in Computer Science ('04), University of Roma "La Sapienza", Italy.
  • Specialization Diploma in Operations Research and Strategic Decisions ('03), University of Roma "La Sapienza", Italy.
  • MS in informatics ('03), University of Pisa, Italy.
  • MS in Computer Science ('94). University of Pisa, Italy.

Research Interests

Professor Roberto's objective is to achieve excellence in cybersecurity research addressing both fundamental and applied challenges in the field, as well as to have impact and to generate innovation. In particular, Professor Roberto's research interests lie in the domain of security and privacy for distributed systems, with a special focus on systems supporting critical infrastructures. He is also interested (among others) in data science, on-line social networks, and application of AI techniques to solve security and privacy issues in current and future systems.

Selected Publications

  • Gabriele Oligeri, Savio Sciancalepore, Simone Raponi, Roberto Di Pietro: PAST-AI: Physical-Layer Authentication of Satellite Transmitters via Deep Learning. IEEE Trans. Inf. Forensics Secur. 18: 274-289 (2023)
  • Savio Sciancalepore, Pietro Tedeschi, Ahmed Aziz, Roberto Di Pietro: Auth-AIS: Secure, Flexible, and Backward-Compatible Authentication of Vessels AIS Broadcasts. IEEE Trans. Dependable Secur. Comput. 19(4): 2709-2726 (2022)
  • Roberto Di Pietro, Simone Raponi, Maurantonio Caprolu, Stefano Cresci: New Dimensions of Information Warfare. Advances in Information Security 84, Springer 2021, ISBN 978-3-030-60617-6, pp. 1-226
  • Pietro Tedeschi, Savio Sciancalepore, Roberto Di Pietro: ARID: Anonymous Remote IDentification of Unmanned Aerial Vehicles. ACSAC 2021: 207-218
  • Andrea De Salve, Paolo Mori, Barbara Guidi, Laura Ricci, Roberto Di Pietro: Predicting Influential Users in Online Social Network Groups. ACM Trans. Knowl. Discov. Data 15(3): 35:1-35:50 (2021)