Federated Learning (FL) approaches for cybersecurity

Our research interests lie in AI and cybersecurity, especially focusing on Federated Learning (FL) approaches. Securing FL poses several challenges related to scalability and attacks that malicious entities (e.g., clients) could carry out (e.g., by providing malicious models to steer the global model).

We are thus looking for motivated candidates, with a PhD degree in Computer Science or related domains, and who would be interested in research items that include, but are not limited to:

• Securing AI or FL applications in a distributed context ;
• Adversarial attacks, e.g., Membership inference attacks (MIA) ;
• Reconstruction attacks.

Scientific visits will be held at IRL ILLS (Montreal, Canada).

The gross salary will range from 3021.50€ to 4664.39€, depending on past work experience.

Profile sought (expected competences and qualifications)
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• PhD or Eng.D. in computer science or related domain (e.g., AI, telecommunications)
• AI and/or cybersecurity.
• Taste for research
• Dynamism, willingness to take initiative
• Team spirit
• Good writing skills
• Good level in written and spoken English