A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks

A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks

The device group based on the Internet of Things (IoT) has been used in face recognition in real life, so it is more necessary to discuss the current data security issues and social hot issues. The Internet of Things device combines edge conditions and many recognizers to generative adversarial netw...

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Main Authors: Wenqiu Zhu, Xiaoyi Wang, Yuezhong Wu, Guang Zou
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2021/6948293
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spelling doaj-b22d9b056eda4cf9956400343ef93fc12021-07-12T02:12:38ZengHindawi-WileyWireless Communications and Mobile Computing1530-86772021-01-01202110.1155/2021/6948293A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial NetworksWenqiu Zhu0Xiaoyi Wang1Yuezhong Wu2Guang Zou3School of Computer ScienceSchool of Computer ScienceSchool of Computer ScienceSchool of Computer ScienceThe device group based on the Internet of Things (IoT) has been used in face recognition in real life, so it is more necessary to discuss the current data security issues and social hot issues. The Internet of Things device combines edge conditions and many recognizers to generative adversarial networks. On the premise of meeting the needs of partial occlusion of users, face recovery is completed through information reorganization. CelebA training set is used to simulate face occlusion, and the model is trained and tested. The results show that the method can recover the complete image of the protection for the facial privacy of specific people. At the same time, the IoT device using this method ensures that the face information is not easy to have tampered with when attacked.http://dx.doi.org/10.1155/2021/6948293
collection DOAJ
language English
format Article
sources DOAJ
author Wenqiu Zhu
Xiaoyi Wang
Yuezhong Wu
Guang Zou
spellingShingle Wenqiu Zhu
Xiaoyi Wang
Yuezhong Wu
Guang Zou
A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks
Wireless Communications and Mobile Computing
author_facet Wenqiu Zhu
Xiaoyi Wang
Yuezhong Wu
Guang Zou
author_sort Wenqiu Zhu
title A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks
title_short A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks
title_full A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks
title_fullStr A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks
title_full_unstemmed A Face Occlusion Removal and Privacy Protection Method for IoT Devices Based on Generative Adversarial Networks
title_sort face occlusion removal and privacy protection method for iot devices based on generative adversarial networks
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8677
publishDate 2021-01-01
description The device group based on the Internet of Things (IoT) has been used in face recognition in real life, so it is more necessary to discuss the current data security issues and social hot issues. The Internet of Things device combines edge conditions and many recognizers to generative adversarial networks. On the premise of meeting the needs of partial occlusion of users, face recovery is completed through information reorganization. CelebA training set is used to simulate face occlusion, and the model is trained and tested. The results show that the method can recover the complete image of the protection for the facial privacy of specific people. At the same time, the IoT device using this method ensures that the face information is not easy to have tampered with when attacked.
url http://dx.doi.org/10.1155/2021/6948293
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