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|Title:||WaC : first results on practical side-channel attacks on commercial machine learning accelerator||Authors:||Won, Yoo-Seung
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
|Issue Date:||2021||Source:||Won, Y., Chatterjee, S., Jap, D., Basu, A. & Bhasin, S. (2021). WaC : first results on practical side-channel attacks on commercial machine learning accelerator. 5th Workshop on Attacks and Solutions in Hardware Security (ASHES '21), 111-114. https://dx.doi.org/10.1145/3474376.3487284||Project:||NRF2018NCR-NCR009-0001||metadata.dc.contributor.conference:||5th Workshop on Attacks and Solutions in Hardware Security (ASHES '21)||Abstract:||Commercial machine learning accelerators like Intel neural Compute Stick 2 (NCS2) enable efficient inference on otherwise low resource edge devices. However, these accelerators are also ex- posed to new threats leveraging physical access. In this paper, we present the first results demonstrating practical electromagnetic side-channel attack on NCS2, allowing secret weight recovery from executed models||URI:||https://hdl.handle.net/10356/153409||DOI:||10.1145/3474376.3487284||Schools:||School of Electrical and Electronic Engineering||Research Centres:||Temasek Laboratories||Rights:||© 2021 Association for Computing Machinery. All rights reserved.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||EEE Conference Papers|
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