On the Transferability of Adversarial Examples Against CNN-Based Image Forensics
Conference Paper1
Authors: Mauro Barni, Kassem Kallas, Ehsan Nowroozi, Benedetta Tondi
Year: 2018
Abstract: Recent studies have shown that Convolutional Neural Networks (CNN) are relatively easy to attack through the generation of so-called adversarial examples. Such vulnerability also affects CNN-based image forensic tools. Research in deep learning has shown that adversarial examples exhibit a certain degree of transferability, i.e., they maintain part of their effectiveness even against CNN models other than the one targeted by the attack……..