We present here the main research topics and activities on the design, security, safety, and robustness of machine learning models developed at the Pattern Recognition and Applications Laboratory (PRALab) of the University of Cagliari. Our findings have significantly contributed to identifying and characterizing the vulnerability of such models to adversarial attacks in the context of real-world applications and proposing robust techniques to make these models more reliable in security-critical scenarios.

Cybersecurity and AI: The PRALab Research Experience

Maura Pintor;Giulia Orru;Davide Maiorca;Ambra Demontis;Gian Luca Marcialis;Battista Biggio;Fabio Roli
2023-01-01

Abstract

We present here the main research topics and activities on the design, security, safety, and robustness of machine learning models developed at the Pattern Recognition and Applications Laboratory (PRALab) of the University of Cagliari. Our findings have significantly contributed to identifying and characterizing the vulnerability of such models to adversarial attacks in the context of real-world applications and proposing robust techniques to make these models more reliable in security-critical scenarios.
2023
Machine Learning; Adversarial Machine Learning; Biometrics; Cybersecurity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/377244
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