7 citations · 7 across the 3 of their papers we have counts for
4 papers
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs
Xinwei Zhao, Matthew C. Stamm
In recent years, convolutional neural networks (CNNs) have been widely used by researchers to perform forensic tasks such as image tampering detection. At the same time, adversaria…
Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers
Xinwei Zhao, Matthew C. Stamm
Recently, physical domain adversarial attacks have drawn significant attention from the machine learning community. One important attack proposed by Eykholt et al. can fool a class…
A Transferable Anti-Forensic Attack on Forensic CNNs Using A Generative Adversarial Network
Xinwei Zhao, Chen Chen, Matthew C. Stamm
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 forger…
Forensic Similarity for Digital Images
Owen Mayer, Matthew C. Stamm
In this paper we introduce a new digital image forensics approach called forensic similarity, which determines whether two image patches contain the same forensic trace or differen…