Design-driven Deception of Face Recognition: An Empirical Study

PETRELLI, Daniela, DULAKE, Nick, MOLINARI, Gianni and CIRAVEGNA, Fabio (2025). Design-driven Deception of Face Recognition: An Empirical Study. ACM Transactions on Computer-Human Interaction. [Article]

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Abstract
This paper takes a design-driven human-centred approach to Face Recognition Technology (FRT). In a process of Research through Design we first generated 120 ways to dodge face recognition, then distilled and tested 50 concepts in the lab. The 19 disguises that successfully bypasses FRT informed the implementation of 7 disguises initially tested with 14 white participants walking through a hall, a corridor, a control gate. The control gate led to a larger study (39 participants of different ethnicities) to assess the effectiveness of the disguises in bypassing 3 open-source FR models using 3 different distance metrics and 4 backends. We compare our real-life evaluation of design-generated disguises against previous and current computing research: while maliciously crafted digital perturbation attacks work well, they do not capture the complexity of live FRT opening up opportunities for future research.
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