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Open AccessArticle

GAN-Based Differential Private Image Privacy Protection Framework for the Internet of Multimedia Things

1
School of Space Information, Space Engineering University, Beijing 101416, China
2
School of Computer Science, University of Technology Sydney, Sydney, NSW 2007, Australia
3
Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou 510006, China
4
Data61, CSIRO, Sydney, NSW 2015, Australia
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(1), 58; https://doi.org/10.3390/s21010058
Received: 24 November 2020 / Revised: 14 December 2020 / Accepted: 19 December 2020 / Published: 24 December 2020
(This article belongs to the Special Issue Security, Trust and Privacy in New Computing Environments)
With the development of the Internet of Multimedia Things (IoMT), an increasing amount of image data is collected by various multimedia devices, such as smartphones, cameras, and drones. This massive number of images are widely used in each field of IoMT, which presents substantial challenges for privacy preservation. In this paper, we propose a new image privacy protection framework in an effort to protect the sensitive personal information contained in images collected by IoMT devices. We aim to use deep neural network techniques to identify the privacy-sensitive content in images, and then protect it with the synthetic content generated by generative adversarial networks (GANs) with differential privacy (DP). Our experiment results show that the proposed framework can effectively protect users’ privacy while maintaining image utility. View Full-Text
Keywords: Internet of Multimedia Things (IoMT); image privacy; object detection; deep learning; generative adversarial network; differential privacy Internet of Multimedia Things (IoMT); image privacy; object detection; deep learning; generative adversarial network; differential privacy
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MDPI and ACS Style

Yu, J.; Xue, H.; Liu, B.; Wang, Y.; Zhu, S.; Ding, M. GAN-Based Differential Private Image Privacy Protection Framework for the Internet of Multimedia Things. Sensors 2021, 21, 58. https://doi.org/10.3390/s21010058

AMA Style

Yu J, Xue H, Liu B, Wang Y, Zhu S, Ding M. GAN-Based Differential Private Image Privacy Protection Framework for the Internet of Multimedia Things. Sensors. 2021; 21(1):58. https://doi.org/10.3390/s21010058

Chicago/Turabian Style

Yu, Jinao; Xue, Hanyu; Liu, Bo; Wang, Yu; Zhu, Shibing; Ding, Ming. 2021. "GAN-Based Differential Private Image Privacy Protection Framework for the Internet of Multimedia Things" Sensors 21, no. 1: 58. https://doi.org/10.3390/s21010058

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