“Related research has made new breakthroughs in the field of facial fraud detection. Experts have proposed an adaptive facial fraud detection model based on Transformer graph representation learning. By alternately stacking graph neural networks and Transformer layers, dynamic K-nearest neighbor dense algorithm and dual attention mechanism are introduced to effectively capture fraud clues, improve model generalization and adaptability, and provide strong support for ensuring facial recognition security.”