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Official PDF TranslationFrontiers of Information Technology & Electronic Engineering

Full-defense framework: multi-level deepfake detection and source tracing

Authors: Hui SHI; Guibin WANG; Yanni LI; Rujia QI

DOI: 10.1631/FITEE_2401012Status: Verified Translated Edition
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Key Findings in This Report

• Proposes a Full-Defense Framework (FDF) that integrates passive detection and proactive defense against deepfake. • Introduces separable watermarks (SepMark) with a robust decoder for source tracing and a semi-robust decoder sensitive to malicious distortions. • Employs cross-domain feature fusion of spatial and frequency channels to improve discrimination between deepfake content and watermark removal attacks. • Achieves dual functionality: copyright protection and deepfake detection even when watermarks are absent, offering a comprehensive defense solution.