A Transferable Anti-Forensic Attack on Forensic CNNs Using A Generative Adversarial Network

Understand

With the development of deep learning, convolutional neural networks (CNNs) have become widely used in multimedia forensics for tasks such as detecting and identifying image forgeries.

• Meanwhile, anti-forensic attacks have been developed to fool these CNN-based forensic algorithms.
• Previous anti-forensic attacks often were designed to remove forgery traces left by a single manipulation operation as opposed to a set of manipulations.
• Additionally, recent research has shown that existing anti-forensic attacks against forensic CNNs have poor transferability, i.e.