Deep Learning for Computational Problems in Hardware Security - Modeling Attacks on Strong Physically Unclonable Function Circuits

The book discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives.