Paper 2025/192

Practical Electromagnetic Fault Injection on Intel Neural Compute Stick 2

Shivam Bhasin, Nanyang Technological University, Singapore
Dirmanto Jap, Nanyang Technological University, Singapore
Marina Krček, Radboud University, The Netherlands
Stjepan Picek, Radboud University, The Netherlands
Prasanna Ravi, Nanyang Technological University, Singapore
Abstract

Machine learning (ML) has been widely deployed in various applications, with many applications being in critical infrastructures. One recent paradigm is edge ML, an implementation of ML on embedded devices for Internet-of-Things (IoT) applications. In this work, we have conducted a practical experiment on Intel Neural Compute Stick (NCS) 2, an edge ML device, with regard to fault injection (FI) attacks. More precisely, we have employed electromagnetic fault injection (EMFI) on NCS 2 to evaluate the practicality of the attack on a real target device. We have investigated multiple fault parameters with a low-cost pulse generator, aiming to achieve misclassification at the output of the inference. Our experimental results demonstrated the possibility of achieving practical and repeatable misclassifications.

Metadata
Available format(s)
PDF
Category
Implementation
Publication info
Published elsewhere. DATE 2025 (Late Breaking Results)
Keywords
EMFIEdge MLModel Evasion
Contact author(s)
sbhasin @ ntu edu sg
djap @ ntu edu sg
marina krcek @ ru nl
stjepan picek @ ru nl
prasanna ravi @ ntu edu sg
History
2025-02-11: approved
2025-02-10: received
See all versions
Short URL
https://ia.cr/2025/192
License
No rights reserved
CC0

BibTeX

@misc{cryptoeprint:2025/192,
      author = {Shivam Bhasin and Dirmanto Jap and Marina Krček and Stjepan Picek and Prasanna Ravi},
      title = {Practical Electromagnetic Fault Injection on Intel Neural Compute Stick 2},
      howpublished = {Cryptology {ePrint} Archive, Paper 2025/192},
      year = {2025},
      url = {https://eprint.iacr.org/2025/192}
}
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