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DOE OSTI · 2339949

IP Protection in TinyML

Zhang, Ning
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Abstract

Tiny machine learning (TinyML) is an essential component of emerging smart microcontrollers (MCUs). How- ever, the protection of the intellectual property (IP) of the model is an increasing concern due to the lack of desktop/server-grade resources on these power-constrained devices. In this paper, we propose STML, a system and algorithm co-design to Secure IP of TinyML on MCUs with ARM TrustZone. Our design jointly optimizes memory utilization and latency while ensuring the security and accuracy of emerging models. We implemented a prototype and benchmarked with 7 models, demonstrating STML reduces 40% of model protection runtime overhead on average.

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BibTeXRIS

Zhang, Ning. 2023-07-09. IP Protection in TinyML. https://www.osti.gov/biblio/2339949

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