Fraunhofer's RealorRender Detects Deepfakes With 85%-91% Accuracy as Fraud Losses Top $1.5 Billion
Updated
Updated · New Atlas · Aug 2
Fraunhofer's RealorRender Detects Deepfakes With 85%-91% Accuracy as Fraud Losses Top $1.5 Billion
1 articles · Updated · New Atlas · Aug 2
Summary
RealorRender, developed at Germany's Fraunhofer IOSB with BSI funding, identified AI-generated images with 85% to 91% accuracy in tests and explains why it reached each verdict.
The system pairs deep-learning classification with image reconstruction: if an AI generator can closely recreate a source image, that reconstruction itself signals the original was likely synthetic.
Heatmaps and segmented image regions show the textures and frequency patterns behind each decision, giving developers a way to audit and improve results rather than relying on a black-box score.
The push for better detection comes as deepfake abuse expands from sexual exploitation to fraud, with 2025 scam losses exceeding $1.5 billion and a 2023 review finding 276,149 sexual deepfakes on one site.