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arXiv · 2506.09777

Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space

Anton Razzhigaev·Matvey Mikhalchuk·Klim Kireev·Igor Udovichenko·Andrey Kuznetsov·Aleksandr Petiushko
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Abstract

Reconstructing facial images from black-box recognition models poses a significant privacy threat. While many methods require access to embeddings, we address the more challenging scenario of model inversion using only similarity scores. This paper introduces DarkerBB, a novel approach that reconstructs color faces by performing zero-order optimization within a PCA-derived eigenface space. Despite this highly limited information, experiments on LFW, AgeDB-30, and CFP-FP benchmarks demonstrate that DarkerBB achieves state-of-the-art verification accuracies in the similarity-only setting, with competitive query efficiency.

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Anton Razzhigaev, Matvey Mikhalchuk, Klim Kireev, Igor Udovichenko, Andrey Kuznetsov, Aleksandr Petiushko. 2025-06-11. Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space. https://arxiv.org/abs/2506.09777

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