Stealing Neural Network Models through the Scan Chain: A New Threat for ML Hardware

Stealing trained machine learning (ML) models is a new and growing concern due to the model's development cost. Existing work on ML model extraction either applies a mathematical attack or exploits hardware vulnerabilities such as side-channel leakage. This paper shows a new style of attack, for the first time, on ML models running on embedded devices by abusing the scan-chain infrastructure. We i...