Fingerprint recognition systems are widely deployed for authentication and forensic applications, but the security of stored fingerprint data remains a critical vulnerability. While many systems avoid storing raw fingerprint images in favor of minutiae-based templates, recent research shows that these templates can be reverse-engineered to reconstruct realistic fingerprint images, enabling physical spoofing attacks that compromise user identities with no means of remediation. We present ProxyPrints, the first practical defense that brings cancellable biometrics to existing fingerprint recognition systems without requiring modifications to proprietary matching software. ProxyPrints acts as a transparent middleware layer between the fingerprint scanner and the matching algorithm, transforming each scanned fingerprint into a consistent, unlinkable alias. This transformation allows biometric identities to be revoked and replaced in the event of a breach, without affecting authentication accuracy. Additionally, ProxyPrints provides organizations with breach detection capabilities by enabling the identification of out-of-band spoofing attempts involving compromised aliases. We evaluate ProxyPrints on standard benchmark datasets and commercial fingerprint recognition systems, demonstrating that it preserves matching performance while offering strong security and revocability. Our open-source implementation includes tools for alias generation and deployment in real-world pipelines, making ProxyPrints a drop-in, scalable solution for fingerprint data protection.

翻译：指纹识别系统广泛应用于身份认证和法医鉴定领域，但存储指纹数据的安全性仍是关键漏洞。尽管许多系统避免存储原始指纹图像，转而采用基于细节点特征的模板，但近期研究表明，这些模板可被逆向工程重构为逼真的指纹图像，从而实施物理伪造攻击，导致用户身份被不可逆地盗用。本文提出ProxyPrints，这是首个为现有指纹识别系统提供可撤销生物特征保护的实际防御方案，无需修改专有匹配软件。ProxyPrints作为指纹扫描仪与匹配算法间的透明中间层，将每次扫描的指纹转换为一致且不可关联的别名。该转换机制允许在数据泄露事件中撤销并替换生物特征身份，同时不影响认证准确性。此外，ProxyPrints通过识别涉及泄露别名的带外伪造尝试，为机构提供数据泄露检测能力。我们在标准基准数据集和商用指纹识别系统上评估ProxyPrints，证明其在保持匹配性能的同时提供强大的安全性和可撤销性。我们的开源实现包含别名生成和实际部署工具，使ProxyPrints成为可即插即用、可扩展的指纹数据保护解决方案。