| 基于可视数据的可信身份识别和认证方法 |
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| 引用本文： | 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. |
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| 作者姓名： | 彭春蕾 高新波 王楠楠 李洁 |
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| 作者单位： | 1. 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，陕西 西安 710071;2. 重庆邮电大学重庆市图像认知重点实验室，重庆 400065 |
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| 基金项目： | 国家重点研发计划基金资助项目(2016QY01W0200);国家重点研发计划基金资助项目(2018AAA0103202);国家自然科学基金资助项目(61806152);陕西省重点研发项目(2020ZDLGY08-08);陕西省自然科学基金资助项目(2019JM-289) |
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| 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。
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| 关 键 词： | 身份识别 可视数据 可信认证 身份匿名化 |
Dependable identity recognition and authorization based on visual information |
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| 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. |
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| Authors: | Chunlei PENG Xinbo GAO Nannan WANG Jie LI |
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| Affiliation: | 1. State Key Laboratory of Integrated Services Networks,Xidian University,Xi’an 710071,China;2. Chongqing Key Laboratory of Image Cognition,Chongqing University of Posts and Telecommunications,Chongqing 400065,China |
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| Abstract: | Recently,deep learning has been widely applied to video and image based identity recognition and authorization tasks,including face recognition and person identification.However,machine learning models,especially deep learning models,can be easily fooled by adversarial attacks,which may cause the identity recognition systems to make a wrong decision.Therefore,dependable identity recognition and authorization has become one of the hot topics currently.Recent advances on dependable identity recognition and authorization from both information space and physical space were presented,where the development of the attack models on face detection,face recognition,person re-identification,and face anti-spoofing as well as printable adversarial patches were introduced.The algorithms of visual identity anonymization and privacy protection were further discussed.Finally,the datasets,experimental protocols and performance of dependable identity recognition methods were summarized,and the possible directions in the future research were presented. |
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| Keywords: | identity recognition visual information dependable recognition identity anonymization |
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