research-article

An Image Privacy Protection Algorithm Based on Adversarial Perturbation Generative Networks

Authors:

Zhigao ZhengAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 2

Article No.: 43, Pages 1 - 14

https://doi.org/10.1145/3381088

Published: 21 April 2021 Publication History

Abstract

Today, users of social platforms upload a large number of photos. These photos contain personal private information, including user identity information, which is easily gleaned by intelligent detection algorithms. To thwart this, in this work, we propose an intelligent algorithm to prevent deep neural network (DNN) detectors from detecting private information, especially human faces, while minimizing the impact on the visual quality of the image. More specifically, we design an image privacy protection algorithm by training and generating a corresponding adversarial sample for each image to defend DNN detectors. In addition, we propose an improved model based on the previous model by training an adversarial perturbation generative network to generate perturbation instead of training for each image. We evaluate and compare our proposed algorithm with other methods on wider face dataset and others by three indicators: Mean average precision, Averaged distortion, and Time spent. The results show that our method significantly interferes with DNN detectors while causing weak impact to the visual quality of images, and our improved model does speed up the generation of adversarial perturbations.

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Cited By

Wang ZHou JWu GLiu SLuo PLi X(2024)Efficient Task-driven Video Data Privacy Protection for Smart Camera Surveillance SystemACM Transactions on Sensor Networks10.1145/362582520:4(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3625825
Si W(2024)Image data privacy protection technology based on reversible information hiding and robust secret sharingIntelligent Systems with Applications10.1016/j.iswa.2024.20039623(200396)Online publication date: Sep-2024
https://doi.org/10.1016/j.iswa.2024.200396
Li HWang JXiong NZhang YVasilakos ALuo X(2023)A Siamese Inverted Residuals Network Image Steganalysis Scheme based on Deep LearningACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357916619:6(1-23)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3579166
Show More Cited By

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An Image Privacy Protection Algorithm Based on Adversarial Perturbation Generative Networks

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 17, Issue 2

May 2021

410 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3461621

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Copyright © 2021 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 April 2021

Online AM: 07 May 2020

Accepted: 01 January 2020

Revised: 01 December 2019

Received: 01 September 2019

Published in TOMM Volume 17, Issue 2

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Project of National Engineering Laboratory for Internet Medical System and Application
the National Natural Science Foundation of China

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Cited By

Wang ZHou JWu GLiu SLuo PLi X(2024)Efficient Task-driven Video Data Privacy Protection for Smart Camera Surveillance SystemACM Transactions on Sensor Networks10.1145/362582520:4(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3625825
Si W(2024)Image data privacy protection technology based on reversible information hiding and robust secret sharingIntelligent Systems with Applications10.1016/j.iswa.2024.20039623(200396)Online publication date: Sep-2024
https://doi.org/10.1016/j.iswa.2024.200396
Li HWang JXiong NZhang YVasilakos ALuo X(2023)A Siamese Inverted Residuals Network Image Steganalysis Scheme based on Deep LearningACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357916619:6(1-23)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3579166
Ou LHe YLiao SQin ZHong YZhang DJia X(2023)FaceIDP: Face Identification Differential Privacy via Dictionary Learning Neural NetworksIEEE Access10.1109/ACCESS.2023.326026011(31829-31841)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3260260
Hupont ITolan SGunes HGómez E(2022)The landscape of facial processing applications in the context of the European AI Act and the development of trustworthy systemsScientific Reports10.1038/s41598-022-14981-612:1Online publication date: 23-Jun-2022
https://doi.org/10.1038/s41598-022-14981-6

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