P315 - BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group

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Konferenzbeitrag
On Brightness Agnostic Adversarial Examples Against Face Recognition Systems
(BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group, 2021) Singh, Inderjeet; Momiyama, Satoru; Kakizaki, Kazuya; Araki, Toshinori
This paper introduces a novel adversarial example generation method against face recognition systems (FRSs). An adversarial example (AX) is an image with deliberately crafted noise to cause incorrect predictions by a target system. The AXs generated from our method remain robust under real-world brightness changes. Our method performs non-linear brightness transformations while leveraging the concept of curriculum learning during the attack generation procedure. We demonstrate that our method outperforms conventional techniques from comprehensive experimental investigations in the digital and physical world. Furthermore, this method enables practical risk assessment of FRSs against brightness agnostic AXs.