arXiv:2604.25071cs.CRcs.AI2026-04

用密码技术保护生物识别数据,防泄露且可扩展。

Scalable Secure Biometric Authentication without Auxiliary Identifiers

论文配图:Scalable Secure Biometric Authentication without Auxiliary Identifiers
图 1 · 摘自论文原文
  • 结合AI与加密技术,无需额外标识实现安全认证。
  • 首次实现大规模无辅助标识的隐私保护生物认证。
  • 适合支付、云端认证等需海量用户安全登录场景。

生物识别认证因便捷性广受青睐,现多用于设备端身份验证。近期系统开始支持云数据库中百万级用户的生物特征认证(如生物支付),但云存储带来重大安全隐患——一旦数据库泄露,所有用户敏感生物信息将被暴露。现有方案或无法有效防护,或因计算开销过大难以部署。本文提出一种新型生物识别认证系统,在保障可证明安全性的同时具备可扩展性与高性能。通过创新融合人工智能与先进密码学技术,并引入多项优化。首次证明了在无辅助标识条件下实现真实世界规模的隐私保护生物识别认证是可行的,有望推动该领域工业应用与后续研究。

原文摘要 · Abstract (English)

The prevalence of biometric authentication has been on the rise due to its ease of use and elimination of weak passwords. To date, most biometric authentication systems have been designed for on-device authentication of the device owner (e.g., smartphones and laptops). Recently, biometric authentication systems have started to emerge that are designed to authenticate users against cloud databases storing representations of biometrics for large numbers of users (potentially millions), such as those facilitating biometric payments. However, the use of a large cloud database introduces a significant attack vector, as a breach of the database could lead to the compromise of all enrolled users' sensitive biometric data. Indeed, all such existing systems either do not adequately protect against such a breach, or are impractical to deploy and use due to their high computational overhead. In this work, we present a new biometric authentication system that provides provable security guarantees against data breaches, while remaining scalable and performant. To do so, we marry artificial intelligence with advanced cryptographic techniques in a novel fashion, providing several optimizations along the way. Our work is the first to show that real-world scalable privacy-preserving biometric authentication without auxiliary identifiers is feasible, and we believe that it will spur widespread industrial adoption and further research in this area.

生物识别加密云安全隐私保护

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