PUF based Secure Computing for Constraint Cyber Physical Object
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Embedded System Security,Hardware Security,Deep Learning,Physical Unclonable Function
The goal of this thesis is to develop new-PUF based, robust and efficient security protocols using machine learning and deep learning techniques.
Informations
Thesis director: Vincent BEROULLE (LCIS)
Thesis supervisor: Giorgio DI NATALE
Thesis started on: Oct. 2019
Thesis defence: Dec. 8th, 2022
Doctoral school: EEATS
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