Polynomial Time Cryptanalytic Extraction of Neural Network Models. (arXiv:2310.08708v1 [cs.LG])

Billions of dollars and countless GPU hours are currently spent on training
Deep Neural Networks (DNNs) for a variety of tasks. Thus, it is essential to
determine the difficulty of extracting all the parameters of such neural
networks when given access to their black-box implementations. Many versions of
this problem have been studied over the last 30 years, and the best current
attack on ReLU-based deep neural networks was presented at Crypto 2020 by
Carlini, Jagielski, and Mironov. It resembles …

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