Is JPEG AI going to change image forensics?

• URL: http://arxiv.org/abs/2412.03261v1
• Date: Wed, 04 Dec 2024 12:07:20 GMT
• Title: Is JPEG AI going to change image forensics?
• Authors: Edoardo Daniele Cannas, Sara Mandelli, Natasa Popovic, Ayman Alkhateeb, Alessandro Gnutti, Paolo Bestagini, Stefano Tubaro,
• Abstract summary: We investigate the counter-forensic effects of the forthcoming JPEG AI standard based on neural image compression. We show that an increase in false alarms impairs the performance of leading forensic detectors when analyzing genuine content processed through JPEG AI.
• Score: 50.92778618091496
• License:
• Abstract: In this paper, we investigate the counter-forensic effects of the forthcoming JPEG AI standard based on neural image compression, focusing on two critical areas: deepfake image detection and image splicing localization. Neural image compression leverages advanced neural network algorithms to achieve higher compression rates while maintaining image quality. However, it introduces artifacts that closely resemble those generated by image synthesis techniques and image splicing pipelines, complicating the work of researchers when discriminating pristine from manipulated content. We comprehensively analyze JPEG AI's counter-forensic effects through extensive experiments on several state-of-the-art detectors and datasets. Our results demonstrate that an increase in false alarms impairs the performance of leading forensic detectors when analyzing genuine content processed through JPEG AI. By exposing the vulnerabilities of the available forensic tools we aim to raise the urgent need for multimedia forensics researchers to include JPEG AI images in their experimental setups and develop robust forensic techniques to distinguish between neural compression artifacts and actual manipulations.

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