Detecting AI-Generated Images Using Facial Similarity and Feature Extraction for Digital Security

Artificial intelligence (AI) has revolutionized digital imagery, enabling the creation of highly realistic AI-generated images. This advancement, however, poses risks, such as fraud and misinformation. A critical gap exists in effectively distinguishing between AI-generated and authentic human images. Here, we propose a robust detection system utilizing facial feature extraction and similarity analysis. Our approach involves a three-stage process, including facial feature extraction, similarity assessment, and final verification using the EfficientNet model. The system achieved an accuracy rate of 96.4%, demonstrating its effectiveness in differentiating between AI-generated and real images. These findings offer significant implications for improving digital security and mitigating the risks posed by AI-generated content.