Toward Robust Proactive Deepfake Detection via Orthogonal Moment Watermarking

This research presents a new method for detecting deepfakes (AI-generated fake videos or images of people) that works better when the forgery techniques differ between training and testing. The approach uses orthogonal moment watermarking (embedding hidden marks in images using mathematical transforms), which stays intact when images are distorted but gets disrupted by deepfake manipulations, allowing the system to achieve 92.58% accuracy in detection.