A New Foe in GPUs: Power Side-Channel Attacks on Neural Network
Proceedings - International Symposium on Quality Electronic Design, ISQED
GPUs have been increasingly adopted as hardware accelerators for neural networks (NN). Prior studies show that the unique execution model and many DC-DC units on GPUs make it uneasy to reverse engineer detailed information of encryption algorithms through power side-channel attacks. However, we observe that a few core parameters of NN can be acquired through power profiling when victim and attacker share a GPU. We discuss potential solutions for the power side-channel attacks on GPUs.
GPU, Neural Network, Side-Channel Attack
Hyeran Jeon, Nima Karimian, and Tamara Lehman. "A New Foe in GPUs: Power Side-Channel Attacks on Neural Network" Proceedings - International Symposium on Quality Electronic Design, ISQED (2021): 313. https://doi.org/10.1109/ISQED51717.2021.9424358