Journal of Information Security Reserach ›› 2024, Vol. 10 ›› Issue (11): 1004-.

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Keytarget Face Recognition Scheme Based on Homomorphic  Encryption and Edge Computing

Liu Jiasen1,2, Wang Xu’an1, Yu Dan2, Li Long2, and Zhao Zhen3   

  1. 1(Key Laboratory for Network and Information Security of the PAP, Engineering University of the PAP, Xi’an 710016)
    2(The Second Mobile Corps under Chinese Armed Police Force, Guangzhou 510800)
    3(School of Cyber Engineering, Xidian University, Xi’an 710071)
  • Online:2024-11-10 Published:2024-11-10

基于同态加密和边缘计算的关键目标人脸识别方案

刘家森1,2王绪安1余丹2李龙2赵臻3   

  1. 1(武警工程大学网络与信息安全武警部队重点实验室西安710016)
    2(中国人民武装警察部队第二机动总队广州510800)
    3(西安电子科技大学网络与信息安全学院西安710071)
  • 通讯作者: 刘家森 硕士,助理工程师.主要研究方向为密码学、云计算、同态加密应用. 869550196@qq.com
  • 作者简介:刘家森 硕士,助理工程师.主要研究方向为密码学、云计算、同态加密应用. 869550196@qq.com 王绪安 博士,教授.主要研究方向为密码学、云计算. wangxazjd@163.com 余丹 硕士,助理工程师.主要研究方向为密码学、管理信息系统. 514926276@qq.com 李龙 助理工程师.主要研究方向为密码学. 814752212@qq.com 赵臻 博士.主要研究方向为公钥密码学和数字签名. zzhen@xidian.edu.cn

Abstract: With the promotion of China’s comprehensive national strength and international status, more and more major international events are held in China’s firsttier cities, such as the 31st Chengdu Universiade and the 19th Hangzhou Asian Games. The huge flow of people and complex crowd categories have caused considerable security pressure on the security team. Because the traditional face recognition system realizes face recognition in the central server in plaintext state and relies on the traditional state secret algorithm to ensure security, the computational efficiency and security of the whole system cannot be fully guaranteed. Therefore, based on the CKKS homomorphic encryption scheme and Insightface face recognition algorithm, this paper proposes a keytarget face recognition scheme supporting edge computing. Firstly, the key face features are encrypted by the CKKS homomorphic encryption scheme, and the ciphertext data are distributed to each frontend monitoring device. After that, the frontend monitoring device is responsible for extracting the face features of the scene crowd and calculating the matching degree with the ciphertext database. Finally, the ciphertext calculation results are returned to the central server and decrypted. Experimental results show that the recognition accuracy of the proposed scheme is 98.2116% when the threshold is 1.23 on LFW data sets, which proves the reliability of the proposed scheme.

Key words: major security activities, keytarget recognition, CKKS homomorphic encryption algorithm, insightface algorithm, edge computing

摘要: 随着我国综合国力和国际地位的提升,越来越多的重大国际活动在我国一线城市举办,如成都大运会和杭州亚运会,庞大的人流量和复杂的人群类别给我国安保队伍造成了不小的安保压力.由于传统的人脸识别系统是在明文状态下在中心服务器中实现人脸识别,并依赖传统国密算法保证安全性,这对整个系统的计算效率和安全性都无法给予充分保障.为此,基于CKKS同态加密方案和Insightface人脸识别算法,提出了一种支持边缘计算的关键目标人脸识别方案.首先利用CKKS同态加密方案对关键目标人脸特征进行加密,并将密文数据分配给各个前端监控设备,之后由前端监控设备负责提取现场人群的人脸特征,并计算与密文数据库的匹配度,最后将密文计算结果返回至中心服务器并进行解密.实验结果表明,该方案在LFW数据集上阈值为1.23时,密文中的识别准确率为98.2116%,证明该方案的可靠性.

关键词: 重大安保活动, 关键目标识别, CKKS同态加密算法, Insightface算法, 边缘计算

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