Clean-Label Attack on Face Authentication Systems Through Rolling Shutter Mechanism

Yufei Wang (Co-first Author), Haoliang Li (Co-first Author), Liepiao Zhang, Yongjian Hu, Alex C. Kot*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

We introduce a novel clean-label black-box face presentation attack on face authentication systems, i.e., face recognition and verification systems, under mild conditions. Different from other clean-label attacks which require inserting complicated or intensity patterns after the image-capturing phase, our designed pattern can be automatically inserted during the exposure by utilizing the rolling shutter mechanism and modulating environment LEDs in a specialized waveform. This method provides a potential way to conduct backdoor attacks in the physical domain. Additionally, we propose an optimization strategy based on evolutionary computing to optimize the parameters of the stripe patterns, enhancing the attack success rate. The experimental results on several face recognition models and face verification services provided by the leading technology companies demonstrate the effectiveness of our attack method. Our study reveals a new attack applicable in the physical world, highlighting significant security concerns for existing face recognition, verification, and face anti-spoofing techniques. © 2024 IEEE.
Original languageEnglish
Pages (from-to)36-40
JournalIEEE Signal Processing Letters
Volume32
Online published7 Nov 2024
DOIs
Publication statusPublished - 2025

Research Keywords

  • Clean-label black-box attack
  • evolutionary computing
  • face recognition/verification
  • rolling shutter

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