The team has expertise in cryptographic methods, algorithms, complexity theory, and neural networks, and includes among its permanent members notable researchers such as Simon Apers, Christina Boura, Geoffroy Couteau, Pierre Fraigniaud, Iordanis Kerenidis, Sophie Laplante, Frédéric Magniez, Claire Mathieu, Micuele Orrù, and Adrian Vladu.

This thesis will focus on the study of adversarial attacks against neural networks, drawing on structural analogies between these models and block ciphers. It will specifically explore the adaptation of classical attack techniques from cryptanalysis — such as differential and linear attacks — to the context of artificial intelligence. The objective is twofold: to identify new types of attacks and to propose appropriate countermeasures to enhance the robustness of these models.