Stanford University; University of Toronto and Vector Institute
Adam Dziedzic, Muhammad Ahmad Kaleem, Yu Shen Lu, Nicolas Papernot
model extraction;model stealing;model functionality stealing;proof-of-work;adversarial machine learning;trustworthy machine learning;deep learning
Increasing the Cost of Model Extraction with Calibrated Proof of Work