Added ML Model Protection Framework for Face Authentication

[J-B-Mugundh]

Description

This PR introduces Trusted Execution and In-Memory ML Model Protection Framework for Face Authentication. Existing approach leaves the ML model vulnerable in the network tab which could be easily reverse engineered. This project addresses the security challenges of deploying ML models for face authentication in a browser context. Our goal is to safeguard the ML model from reverse engineering and tampering while ensuring that security measures do not significantly impact the model’s size or degrade the user experience.

Implementation video: https://drive.google.com/file/d/1nxCbaACXoYc-8x8itIlNNrkBSSGWqFWZ/view?usp=drive_link

Fixes #1261

Type of change

• Added a new machine learning frameworks, libraries or software.
• Documentation update

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊