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MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection., , and . HOST, page 197-208. IEEE, (2020)Hardware-Software Co-design for Side-Channel Protected Neural Network Inference., , , , and . HOST, page 155-166. IEEE, (2023)Hands-On Teaching of Hardware Security for Machine Learning., , , , and . ACM Great Lakes Symposium on VLSI, page 455-461. ACM, (2022)An Efficient 3D Face Recognition Algorithm., , , , , , and . NTMS, page 1-5. IEEE, (2009)Guarding Machine Learning Hardware Against Physical Side-Channel Attacks., , , and . CoRR, (2021)Trustworthy AI Inference Systems: An Industry Research View., , , , , , , , , and 18 other author(s). CoRR, (2020)BoMaNet: Boolean Masking of an Entire Neural Network., , and . ICCAD, page 51:1-51:9. IEEE, (2020)High-Fidelity Model Extraction Attacks via Remote Power Monitors., , , and . AICAS, page 328-331. IEEE, (2022)MaskedNet: A Pathway for Secure Inference against Power Side-Channel Attacks., , and . CoRR, (2019)Guarding Machine Learning Hardware Against Physical Side-channel Attacks., , , and . ACM J. Emerg. Technol. Comput. Syst., 18 (3): 56:1-56:31 (2022)