电信科学 ›› 2020, Vol. 36 ›› Issue (11): 1-17.doi: 10.11959/j.issn.1000-0801.2020293
• 综述 • 下一篇
修回日期:
2020-11-10
出版日期:
2020-11-20
发布日期:
2020-12-09
作者简介:
彭春蕾(1991- ),男,博士,西安电子科技大学综合业务网理论及关键技术国家重点实验室讲师,主要研究方向为计算机视觉、模式识别和机器学习|高新波(1972- ),男,博士,重庆邮电大学重庆市图像认知重点实验室教授,主要研究方向为多媒体分析、计算机视觉、模式识别与机器学习等|王楠楠(1986- ),男,博士,西安电子科技大学综合业务网理论及关键技术国家重点实验室教授,主要研究方向为计算机视觉、模式识别和机器学习|李洁(1972- ),女,博士,西安电子科技大学综合业务网理论及关键技术国家重点实验室教授,主要研究方向为模式识别和计算机视觉
基金资助:
Chunlei PENG1,Xinbo GAO2(),Nannan WANG1,Jie LI1
Revised:
2020-11-10
Online:
2020-11-20
Published:
2020-12-09
Supported by:
摘要:
近年来,深度学习技术在基于视频和图像等可视数据的身份识别和认证任务(如人脸、行人识别等)中得到了广泛应用。然而,机器学习(特别是深度学习模型)容易受到特定的对抗攻击干扰,从而误导身份识别系统做出错误的判断。因此,针对身份识别系统的可信认证技术研究逐渐成为当前的研究热点。分别从基于信息空间和物理空间的可视数据身份识别和认证攻击方法展开介绍,分析了针对人脸检测与识别系统、行人重识别系统的攻击技术及进展,以及基于人脸活体伪造和可打印对抗图案的物理空间攻击方法,进而讨论了可视数据身份匿名化和隐私保护技术。最后,在简要介绍现有研究中采用的数据库、实验设置与性能分析的基础上,探讨了可能的未来研究方向。
中图分类号:
彭春蕾,高新波,王楠楠,李洁. 基于可视数据的可信身份识别和认证方法[J]. 电信科学, 2020, 36(11): 1-17.
Chunlei PENG,Xinbo GAO,Nannan WANG,Jie LI. Dependable identity recognition and authorization based on visual information[J]. Telecommunications Science, 2020, 36(11): 1-17.
表1
信息空间的可视数据身份识别攻击实验概况"
任务描述 | 代表性方法 | 实验数据库 | 被攻击模型 |
攻击人脸识别系统 | 参考文献[ | CASIA-WebFace[ | SphereFace[ |
参考文献[ | CASIA-WebFace[ | FaceNet[ | |
参考文献[ | CelebA[ | VGG-Face[ | |
攻击行人重识别系统 | 参考文献[ | Market-1501[ | HACNN[ |
参考文献[ | Market-1501[ | BOT[ | |
攻击步态识别系统 | 参考文献[ | CASIA-A[ | CNN-Gait[ |
参考文献[ | CASIA-B[ | GaitSet[ |
表2
物理空间的可视数据身份识别攻击实验概况"
任务描述 | 代表性方法 | 实验数据库 | 被攻击模型 |
打印眼镜图案,攻击人脸识别系统 | 参考文献[ | 自建数据库 | OpenFace[ |
打印帽沿图案,攻击人脸识别系统 | 参考文献[ | CASIA-WebFace[ | ArcFace[ |
打印纸板图案,攻击行人检测系统 | 参考文献[ | Inria[ | YOLOv2[ |
打印上衣图案,攻击行人检测系统 | 参考文献[ | 自建数据库 | Faster R-CNN[ |
打印上衣图案,攻击行人重识别系统 | 参考文献[ | Market-1501[ | 行人重识别算法 |
打印背景板图案,攻击行人检测系统 | 参考文献[ | 自建数据库 | GOTURN[ |
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