Intentional Electromagnetic Interference Attacks on Facial Recognition
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Computer Science > Computer Vision and Pattern Recognition
arXiv:2607.15512 (cs)
[Submitted on 16 Jul 2026]
Title:Intentional Electromagnetic Interference Attacks on Facial Recognition
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Abstract:Attacks on general computer vision algorithms are often relegated to the digital domain, with the optimization performed purely in the digital world and then translated to physical mediums for implementation. In the field of biometrics, including facial recognition, physical presentation attacks targeting biometric sensors are dominant and present significant opportunity and risk. This paper highlights a critical vulnerability in the physical-to-digital pipeline of biometric sensors and provides a standardized approach for testing facial recognition system robustness against hardware attacks, going beyond and potentially complementing presentation attacks (as defined in ISO/IEC 30107 standard series). Specifically, in this work we (a) demonstrate that intentional electromagnetic interference is possible to be conducted with commonly accessible radio frequency (RF) equipment, (b) assess the robustness of state-of-the-art face recognition methods against RF-based attacks, and (c) provide a dataset composed of face images captured with and without electromagnetic interference to serve as a new benchmark for testing modern face matchers against RF-sourced interference.
| Comments: | To be published in IEEE/IAPR IJCB (International Joint Conference on Biometrics) 2026 |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Cryptography and Security (cs.CR); Machine Learning (cs.LG) |
| Cite as: | arXiv:2607.15512 [cs.CV] |
| (or arXiv:2607.15512v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2607.15512
arXiv-issued DOI via DataCite (pending registration)
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Submission history
From: Tyler Fitzsimmons [view email][v1] Thu, 16 Jul 2026 23:55:15 UTC (13,233 KB)
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