19 February 2014 Image counter-forensics based on feature injection
Author Affiliations +
Abstract
Starting from the concept that many image forensic tools are based on the detection of some features revealing a particular aspect of the history of an image, in this work we model the counter-forensic attack as the injection of a specific fake feature pointing to the same history of an authentic reference image. We propose a general attack strategy that does not rely on a specific detector structure. Given a source image x and a target image y, the adversary processes x in the pixel domain producing an attacked image ~x, perceptually similar to x, whose feature f(~x) is as close as possible to f(y) computed on y. Our proposed counter-forensic attack consists in the constrained minimization of the feature distance Φ(z) =│ f(z) - f(y)│ through iterative methods based on gradient descent. To solve the intrinsic limit due to the numerical estimation of the gradient on large images, we propose the application of a feature decomposition process, that allows the problem to be reduced into many subproblems on the blocks the image is partitioned into. The proposed strategy has been tested by attacking three different features and its performance has been compared to state-of-the-art counter-forensic methods.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Iuliani, S. Rossetto, T. Bianchi, Alessia De Rosa, A. Piva, M. Barni, "Image counter-forensics based on feature injection", Proc. SPIE 9028, Media Watermarking, Security, and Forensics 2014, 902810 (19 February 2014); doi: 10.1117/12.2042234; https://doi.org/10.1117/12.2042234
PROCEEDINGS
15 PAGES


SHARE
Back to Top