Focus on Finding Deepfakes: A Robust Proactive Detection Method Based on Orthogonal Moment Watermarking

Deepfake detection remains a challenging research topic, especially when the quality of forged images degrades, leading to unreliable detection results. In this paper, we propose a watermarking-based proactive method for robust proactive deepfake detection. First, we embed a watermark into the Fractional-order Quaternion Exponent Moments (FrQEMs) space of the host face image, achieving a balance between imperceptibility and robustness of the watermarking algorithm. Then, we introduce the Frequency Mamba (FreMamba) block to enhance feature extraction by leveraging correlations between frequency-domain subbands, thereby enabling the extraction of more discriminative feature representations. Finally, at the…

• NN
  National Natural Science Foundation of China

  Awards: 62302249, 62541206, 62272255, 62406051, 62502250
• NS
  Natural Science Foundation of Shandong Province

  Award: ZR2023QF032
• KS
  Key Science and Technology Foundation of Gansu Province

  Awards: 2025QZJH02, 2023CXGC010102, 2023TZXD049