基于全同态加密的人脸特征密文认证系统

杨雄; 张晓惠

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基于全同态加密的人脸特征密文认证系统

更新时间：2026-09-04

- 基于全同态加密的人脸特征密文认证系统
- Face feature ciphertext authentication system based on fully homomorphic encryption
- 微电子学与计算机 2020年37卷第9期页码：56-61
- 作者机构：
  
  福州大学至诚学院计算机工程系,福建,福州,350002
- 作者简介：
- 基金信息：
  
  2019年福州大学至诚学院省基金培育项目 KJ20190042017年福建省教育厅青年基金项目 JAT170854
- DOI：
  中图分类号：
- 纸质出版：2020
- 稿件说明：
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杨雄, 张晓惠. 基于全同态加密的人脸特征密文认证系统[J]. 微电子学与计算机, 2020, 37(9): 56-61.

YANG Xiong, ZHANG Xiao-hui. Face feature ciphertext authentication system based on fully homomorphic encryption[J]. 2020, 37(9): 56-61.
杨雄, 张晓惠. 基于全同态加密的人脸特征密文认证系统[J]. 微电子学与计算机, 2020, 37(9): 56-61. DOI：

YANG Xiong, ZHANG Xiao-hui. Face feature ciphertext authentication system based on fully homomorphic encryption[J]. 2020, 37(9): 56-61. DOI：

摘要

随着人脸识别系统的广泛采用，基于人脸识别的身份认证系统必须充分考虑用户人脸特征的安全性.为防止人脸特征泄漏，人脸特征不能以明文形式进行操作和存储.针对此问题，设计了基于全同态加密的人脸特征密文认证系统，该系统在加密域中进行人脸特征匹配，同时数据库中保存的是人脸特征模板的同态密文，整个系统无需解密人脸特征模板就可完成认证.系统实现部分借助了微软的开源简单加密算法函数库，并进一步探索了一种批处理和降维的方案，以权衡人脸匹配的准确性和计算复杂性.基于人脸基准数据库(LFW、IJB-A、IJB-B、CASIA)的测试结果表明，基于全同态加密的人脸特征密文认证是可行的，能够基本满足真实应用场景的需求.

Abstract

With the widespread adoption of face recognition systems

identity authentication systems based on face recognition must fully consider the security of user face features. To prevent face feature leakage

face features cannot be manipulated and stored in clear text. Aiming at this problem

a face-character ciphertext authentication system based on fully homomorphic encryption is designed. The system performs face feature matching in the encrypted domain. At the same time

the database stores the homomorphic ciphertext of the face feature template. The whole system Authentication can be done without decrypting the face feature template. The system implementation part relies on Microsoft′s open source simple encryption algorithm library

and further explores a batch and dimension reduction scheme to balance the accuracy and computational complexity of face matching. The test results based on face reference database (LFW

IJB-A

IJB-B

CASIA) show that face-based ciphertext authentication based on fully homomorphic encryption is feasible and can basically meet the needs of real application scenarios.

关键词

Keywords

references

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LIU Z, PING L, WANG X, et al. Deep Learning Face Attributes in the Wild[C]//International Conference on Computer Vision.Santiago: IEEE, 2015: 3730-3738.

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TAIGMAN Y, YANG M, RANZATO M, et al.DeepFace: Closing the Gap to Human-Level Performance in Face Verification[C]//Computer Vision and Pattern Recognition.Columbus: IEEE, 2014: 1701-1708.

ZHAO Q S, ZENG Q K, LIU X M, et al.Verifiable Computation Using Re-randomizable Garbled Circuits[J]. Journal of Software, 2019, 30(2):209-225. DOI: 209

YU L Z, LIN G X, JIE G Y, et al. Survey on Homomorphic Encryption Algorithm and Its Application in the Privacy-Preserving for Cloud Computing[J]. Journal of Software, 2018, 29(7):1830-1851. DOI: 1830

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FONTAINE C, GALAND F. A Survey of Homomorphic Encryption for Nonspecialists[J].EURASIP Journal on Information Security, 2007(1):1-10. DOI: 1

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