Face Re-morphing: Differential Morphing Attack Detection via Feature-Space Similarity Changes

2026-08-13

AI Summary

This study addresses the performance limitations of existing face morphing attack detection methods that rely predominantly on static features. We propose a novel detection framework leveraging similarity variations induced by re-morphing operations. Specifically, this work pioneers the utilization of feature space response discrepancies caused by secondary morphing as complementary discriminative cues, achieving precise identification through image re-morphing generation and cosine similarity analysis. Extensive experiments demonstrate that the proposed method exhibits robust generalization across multiple datasets and models, with particularly superior performance on the AMSL and FEI Morph datasets. By effectively overcoming the bottlenecks inherent in traditional static detection approaches, this research establishes a new paradigm for defending against face morphing attacks.

Abstract

Face morphing attacks pose a serious threat to face recognition systems because a single morphed document image can be matched to multiple contributors. Differential morphing attack detection (D-MAD) addresses this threat by comparing a document image with a trusted live image, but existing methods often rely on static feature differences, constituent-face reconstruction, or multi-cue fusion. This paper proposes Face Re-morphing, a D-MAD method that uses the feature-space response to an additional morphing operation as a detection cue. Given a document image and a trusted live image, the proposed method generates a re-morphed image and uses the change between the document--live and live--re-morphed cosine similarities as the detection score. Experiments on FRLL-Morphs and FEI Morph show that the proposed cue is effective across different morphing conditions, re-morphing methods, and face recognition models. Comparisons with existing methods show favorable results on AMSL and indicate that the proposed method performs well under the Criminal condition on FEI Morph Version~1, particularly when using MorDIFF. These results indicate that re-morphing-induced similarity change provides a complementary cue for D-MAD.

Problem

• Differential Morphing Attack Detection
• Face Recognition Security
• Morphing Attack
• D-MAD

Innovation

• Face Re-morphing
• Differential Morphing Attack Detection
• Feature-Space Similarity Changes
• Re-morphing-induced Cue
• Cosine Similarity Delta