arXiv:2605.03857cs.CVcs.CR2026-05

改进人脸模板保护的不可逆性,提升隐私安全。

A Deeper Dive into the Irreversibility of PolyProtect: Making Protected Face Templates Harder to Invert

论文配图:A Deeper Dive into the Irreversibility of PolyProtect: Making Protected Face Templates Harder to Invert
图 1 · 摘自论文原文
  • 用可调重叠的多项式变换增强模板不可逆性
  • 新密钥选择算法使逆向攻击难度显著提高
  • 适合作为生物特征保护系统设计参考

本文深入分析了PolyProtect在人脸嵌入保护中的不可逆性。该方法通过多变量多项式将嵌入转换为受保护模板,其系数与指数对每位用户唯一。研究发现,基于余弦距离的数值求解器比早期使用的欧氏距离更易逆向生成模板。为此,提出一种密钥选择算法,旨在选取能提升不可逆性的多项式参数,相比纯随机密钥效果更优。实验表明,该算法有效提升了模板抗逆向能力,并使不同重叠参数下的不可逆性趋于一致,从而更好控制不可逆性与识别准确率之间的权衡。此外,嵌入元素取值范围会影响识别精度,但预归一化处理可改善此问题。代码已开源,确保可复现性。

原文摘要 · Abstract (English)

This work presents a deeper analysis of the "irreversibility" property of PolyProtect, a biometric template protection method initially proposed for securing face embeddings. PolyProtect transforms embeddings into protected templates via multivariate polynomials, whose coefficients and exponents are distinct for each subject enrolled in the face recognition system. A polynomial is applied to consecutive sets of elements from a given embedding, where the amount of overlap between the sets is a tunable parameter. We begin our irreversibility analysis by demonstrating that PolyProtected templates are easier to invert using a numerical solver based on cosine distance, as opposed to Euclidean distance (used in the earlier PolyProtect work). To make this inversion more difficult, we then propose a "key selection algorithm", which tries to choose "keys" (coefficients and exponents of the PolyProtect polynomial) that enhance the irreversibility of PolyProtected templates, compared to when the keys are purely random. Our experiments show that this algorithm is effective at generating PolyProtected templates that are significantly more difficult to invert, and that it approximately equalises the irreversibility of PolyProtected templates generated using different "overlap" parameters. This allows for better control of the irreversibility versus accuracy trade-off, known to exist across different overlaps. We also show that accuracy in the PolyProtected domain can be affected by the range in which the embedding elements lie, but that this can be improved by normalizing the embeddings prior to applying PolyProtect. This work is reproducible using our open-source code.

生物特征保护不可逆性人脸识别隐私安全

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