[Technical Verification] Architecture of a "Robust AI Image Authenticity Verification System" Built with Gemini 2.5 Flash x C2PA x Multiple Models

This article from Zenn GenAI details the architecture of an AI image authenticity verification system. It addresses the growing challenge of distinguishing between human-created and AI-generated images. The author proposes a "fight fire with fire" approach, using AI to detect AI-generated content. The system, named "Evidence Lens," leverages Gemini 2.5 Flash, C2PA (Content Authenticity Initiative), and multiple models to ensure stability and reliability. The article likely delves into the technical aspects of the system's design, including model selection, data processing, and verification mechanisms. The focus on C2PA suggests an emphasis on verifiable credentials and provenance tracking to combat deepfakes and misinformation. The use of multiple models likely aims to improve accuracy and robustness against adversarial attacks.

• •AI can be used to verify the authenticity of images.
• •The system uses Gemini 2.5 Flash, C2PA, and multiple models.
• •The goal is to create a robust and reliable image verification system.