LightLSB：算力受限环境下大规模生物特征图像的轻量级安全传输机制

张登辉; 沈圣尚; 姚捷凤; 李默涵; 李爱平

doi:10.11959/j.issn.2096-109x.2025016

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LightLSB：算力受限环境下大规模生物特征图像的轻量级安全传输机制

学术论文 | 更新时间：2025-05-14

- LightLSB：算力受限环境下大规模生物特征图像的轻量级安全传输机制
- LightLSB: a lightweight secure transmission mechanism for large-scale biometric images in computing limited environment
- 网络与信息安全学报 2025年11卷第2期页码：61-75
- 作者机构：
  
  1.广州大学网络空间安全学院，广东广州 510006
  2.齐鲁工业大学（山东省科学院）算力互联网与信息安全教育部重点实验室，山东济南 250353
  3.国防科技大学计算机学院，湖南长沙 410073
- 作者简介：
  
  [ "张登辉（1988- ），男，河南信阳人，广州大学副教授，主要研究方向为图像安全和人工智能模型评测。" ]
  [ "沈圣尚（2000- ），男，广东信宜人，广州大学硕士生，主要研究方向为图像安全和有损图像修复。" ]
  [ "姚捷凤（2000- ），男，广东广州人，广州大学硕士生，主要研究方向为视觉秘密共享和图像安全。" ]
  [ "李默涵（1987- ），女，甘肃兰州人，广州大学教授，主要研究方向为人工智能安全和网络入侵检测。" ]
  [ "李爱平（1974- ），男，山东诸城人，国防科技大学研究员，主要研究方向为大数据分析、数据挖掘和网络信息安全。" ]
- 基金信息：
  
  国家重点研发计划(2019YFB1706003);广东省自然科学基金(2214050004382);教育部人文社科青年基金项目(23YJCZH291);算力互联网与信息安全教育部重点实验室课题(2023ZD02)
- DOI：10.11959/j.issn.2096-109x.2025016
  中图分类号： TP393
- 收稿：2024-12-25，
  
  修回：2025-02-28，
  
  纸质出版：2025-04-25
- 稿件说明：
移动端阅览
张登辉, 沈圣尚, 姚捷凤, 等. LightLSB:算力受限环境下大规模生物特征图像的轻量级安全传输机制[J]. 网络与信息安全学报, 2025, 11(2): 61-75.

ZHANG D H, SHEN S S, YAO J F, et al. LightLSB: a lightweight secure transmission mechanism for large-scale biometric images in computing limited environment[J]. Chinese Journal of Network and Information Security, 2025, 11(2): 61-75.
张登辉, 沈圣尚, 姚捷凤, 等. LightLSB:算力受限环境下大规模生物特征图像的轻量级安全传输机制[J]. 网络与信息安全学报, 2025, 11(2): 61-75. DOI： 10.11959/j.issn.2096-109x.2025016.

ZHANG D H, SHEN S S, YAO J F, et al. LightLSB: a lightweight secure transmission mechanism for large-scale biometric images in computing limited environment[J]. Chinese Journal of Network and Information Security, 2025, 11(2): 61-75. DOI： 10.11959/j.issn.2096-109x.2025016.

摘要

近年来，以人脸识别为代表的生物特征识别技术越来越多地出现在社会生活中。物联网智能终端之间的互联互通使随时随地大规模收集用户生物特征数据成为可能，也为海量数据的安全应用带来新的挑战。与通用计算设备相比，物联网终端设备日趋小型化和轻量化，难以支撑标准密码学所需的复杂运算。生物特征技术的广泛使用加剧了社会对个人信息隐私泄露的担忧。针对上述问题，提出了一种基于可视密码的轻量级生物特征图像安全传输机制LightLSB。LightLSB复用现有可视密码方法，在预处理和后处理过程中逐步提升解密图像质量。通过将敏感生物特征图像分割为多张与原始图像无关的分存图像，在不可信网络中实现了大规模生物特征图像的安全传输。在5个典型的生物特征数据集上开展了实验，实验结果表明，所提架构可以在加密数据集上实现与普通数据集相同的识别性能。

Abstract

In recent years

face recognition and other biometric recognition technologies have been increasingly appearing in social life. The interconnection of intelligent terminals in the Internet of things (IoT) has made it possible to collect biometrics on a large scale anytime and anywhere

which has also brought new challenges to the privacy protection of massive data. Compared with general computing devices

IoT terminal equipment has been becoming smaller and lighter

making it difficult to support the complex operations required by standard cryptography. The widespread use of biometric recognition has intensified social concerns about personal privacy disclosure. To address these problems

a lightweight secure transmission mechanism for large-scale biometric images (LightLSB) was proposed. The existing visual cryptography algorithm was reused

and the quality of decrypted images was gradually improved during preprocessing and post-processing. By dividing sensitive biometric images into multiple shares unrelated to the original image

the secure transmission of large-scale biometric images was realized in untrusted networks. Experiments were carried out on three typical biometric datasets

and the results showed that the proposed framework could achieve the same recognition performance on encrypted datasets as on ordinary datasets.

关键词

Keywords

references

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