Image Description Matcher

Privacy, Trust, and Monetization with Confidential AI.

GitHub Repository

What problem does it solve?

This PoC showcases how AI-powered verification can run along with processed data in Trusted Execution Environments (TEEs). It turns trust into a selling point, enabling creators and data owners to monetize their protected content securely and with verifiable confidence.

How does it work?

The Protected Image is Uploaded

The content creator encrypts an image as protected data and provides a description.

The AI Model Analyzes the Content

An AI model runs inside a TEE, analyzing the decrypted image without having access to the encryption key.

Monetization and Data Controls

Content creators can share insights from data without revealing the original file, enhancing trust in monetization mechanisms.

How to use it

1
The Protected Image is Uploaded
The content creator encrypts an image as protected data and provides a description.
2
The AI Model Analyzes the Content
An AI model runs inside a TEE, analyzing the decrypted image without having access to the encryption key.
3
A Similarity Score is Generated
The AI model compares the provided description with the actual image and produces a trust score.
4
Results Delivered Securely
The result is sent to the user, ensuring verification without exposing the original data.

Going Further

AI-Powered Content Validation

Imagine an AI agent that detects fraudulent content or misleading metadata on decentralized social media platforms.Enhance trust in digital marketplaces where metadata accuracy is key.

AI Against Information Overload

AI helps streamline content analysis, ranking posts, and filtering information efficiently.

Expanding Beyond Images

Apply the same framework to analyze and validate text, videos, or datasets. Transform the PoC into a general-purpose AI analysis tool for automated content validation.