On the Transferability of Adversarial Examples Against CNN-Based Image
Forensics

On the Transferability of Adversarial Examples Against CNN-Based Image Forensics

5 November 2018

ArXiv (abs)PDF HTML

Papers citing "On the Transferability of Adversarial Examples Against CNN-Based Image Forensics"

10 / 10 papers shown

Title
Resisting Deep Learning Models Against Adversarial Attack Transferability via Feature Randomization Ehsan Nowroozi Mohammadreza Mohammadi Pargol Golmohammadi Yassine Mekdad Mauro Conti Selcuk Uluagac AAML SILM 82 14 0 11 Sep 2022
Making DeepFakes more spurious: evading deep face forgery detection via trace removal attack Chi Liu Huajie Chen Tianqing Zhu Jun Zhang Wanlei Zhou AAML 69 24 0 22 Mar 2022
Demystifying the Transferability of Adversarial Attacks in Computer Networks Ehsan Nowroozi Yassine Mekdad Mohammad Hajian Berenjestanaki Mauro Conti Abdeslam El Fergougui AAML 100 35 0 09 Oct 2021
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs Xinwei Zhao Matthew C. Stamm AAML 49 4 0 26 Jan 2021
Perception Matters: Exploring Imperceptible and Transferable Anti-forensics for GAN-generated Fake Face Imagery Detection Yongwei Wang Xin Ding Li Ding Rabab Ward Z. J. Wang AAML 41 21 0 29 Oct 2020
A Survey of Machine Learning Techniques in Adversarial Image Forensics Ehsan Nowroozi Ali Dehghantanha R. Parizi K. Choo AAML 69 73 0 19 Oct 2020
Adversarial Attack on Deep Learning-Based Splice Localization Andras Rozsa Zheng Zhong Terrance E. Boult AAML 43 4 0 17 Apr 2020
Media Forensics and DeepFakes: an overview L. Verdoliva 112 556 0 18 Jan 2020
SpoC: Spoofing Camera Fingerprints D. Cozzolino Justus Thies Andreas Rossler Matthias Nießner L. Verdoliva 87 39 0 27 Nov 2019
Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examples Mauro Barni Ehsan Nowroozi B. Tondi Bowen Zhang AAML 60 17 0 25 Oct 2019