通过同态加密来确保步态识别.
Marina Banov1,2, Domagoj Pinčić1, Diego Sušanj3
1Faculty of Engineering, University of Rijeka, Vukovarska 58, Rijeka, 51000, Croatia.
Scientific reports
|August 12, 2025
概括
同型加密 (HE) 在步态识别过程中保护生物识别数据. 这种方法可以在保持准确性的同时进行安全分类,尽管它需要与计算性能进行权衡.
科学领域:
- 生物识别和网络安全
- 应用密码学 应用密码学
- 机器学习 机器学习
背景情况:
- 生物识别系统提供了强大的安全性,但由于无法撤销被泄露的数据,造成隐私风险.
- 目前的系统往往需要敏感的生物识别数据被解密处理,增加脆弱性.
- 在生物识别中,对保护隐私的技术的需求至关重要.
研究的目的:
- 探索同型加密 (HE) 的应用,以保护生物识别数据在分类阶段.
- 开发和评估使用HE的安全步态识别系统.
- 分析HE对系统准确性和计算复杂性的影响.
主要方法:
- 设计了一个系统,其中有一个局部特征提取器 (视觉变压器) 和一个HE兼容的分类器处理加密数据.
- 在步态识别任务中证明了可行性.
- 进行统计分析以评估准确性和计算开销,考虑各种激活函数及其多项式近似值.
主要成果:
- 该研究证实了使用同态加密技术实现安全和准确的步态识别的可行性.
- 量化了HE对分类准确性和计算复杂性的影响.
- 确定了与不同激活函数相关的性能权衡,以及它们在HE中的近似值.
结论:
- 同型加密是一种可行的技术,用于提高生物识别系统的隐私,特别是用于步态识别.
- 拟议的系统为安全的生物识别数据处理提供了一个有希望的方向.
- 需要仔细考虑激活函数及其近似值,以平衡安全性和计算效率.
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