CIPHER: Counterfeit Image Pattern High-level Examination via Representation

1. 1Examine high-level representations of images to identify patterns indicative of counterfeit generation
2. 2Utilize GANs and diffusion models to generate synthetic faces for training and testing CIPHER
3. 3Develop and fine-tune CIPHER to remain robust across diverse generative models
4. 4Evaluate CIPHER's performance on various datasets and scenarios to ensure its effectiveness

AI engineers and researchers working on image forensics and cybersecurity can benefit from CIPHER to develop robust detectors against misinformation and fraud, while data scientists can apply this technique to improve image authenticity verification

💡 High-level representation examination can effectively detect counterfeit images generated by GANs and diffusion models

📸 CIPHER detects fake images! 🚫