Informations générales
Intitulé de l'offre : PhD Student – Adversarial Attacks on Neural Networks [M/F] (H/F)
Référence : UMR8243-MELGOD-005
Nombre de Postes : 1
Lieu de travail : PARIS 13
Date de publication : vendredi 11 juillet 2025
Type de contrat : CDD Doctorant
Durée du contrat : 36 mois
Date de début de la thèse : 1 octobre 2025
Quotité de travail : Complet
Rémunération : 2200 gross monthly
Section(s) CN : 06 - Sciences de l'information : fondements de l'informatique, calculs, algorithmes, représentations, exploitations
Description du sujet de thèse
This PhD thesis will focus on the study of adversarial attacks against neural networks, based on structural analogies between these models and block ciphers. It will specifically explore how classical cryptanalysis techniques—such as differential and linear attacks—can be transposed into the context of artificial intelligence. The goal is twofold: to identify new types of attacks and to propose appropriate countermeasures to strengthen model robustness.
Contexte de travail
The team has expertise in cryptographic methods, algorithms, complexity theory, and neural networks. Its permanent members include prominent researchers such as Simon Apers, Christina Boura, Geoffroy Couteau, Pierre Fraigniaud, Iordanis Kerenidis, Sophie Laplante, Frédéric Magniez, Claire Mathieu, Micuele Orrù, and Adrian Vladu.
Contraintes et risques
No identified risks or constraints