Professor, University of Genova, Italy. Director of PRALab, University of Cagliari, Italy
19th July 2022, 4:00pm - 5:00pm (GST)
Adversarial Machine Learning
Machine-learning algorithms are widely used for cybersecurity applications, including spam, malware detection, biometric recognition. In these applications, the learning algorithm must face intelligent and adaptive attackers who can carefully manipulate data to purposely subvert the learning process. As machine learning algorithms have not been originally designed under such premises, they have been shown to be vulnerable to well-crafted attacks, including test-time evasion and training-time poisoning attacks (also known as adversarial examples). This talk aims to introduce the fundamentals of adversarial machine learning and some techniques to assess the vulnerability of machine-learning algorithms to adversarial attacks. We report application examples including object recognition in images, biometric identity recognition, spam, and malware detection.
Fabio Roli is Full Professor of Computer Engineering at the University of Genova, Italy. He is founding Director of the Pattern Recognition and Applications laboratory at the University of Cagliari (https://pralab.diee.unica.it/). He is partner of the company Pluribus One that he co-founded (https://www.pluribus-one.it). He has been doing research on the design of pattern recognition and machine learning systems for thirty years. He has been appointed Fellow of the IEEE and Fellow of the International Association for Pattern Recognition. He was a recipient of the Pierre Devijver Award for his contributions to statistical pattern recognition and 2020 “Pattern Recognition Medal” of the international journal Pattern Recognition. He was a member of NATO advisory panel for Information and Communications Security, NATO Science for Peace and Security (2008 – 2011).