⏳Future

As we continue refining and enhancing our system, several key improvements and optimizations are under consideration. These enhancements aim to improve scalability, security, and usability.

1. Using Zero-Knowledge Proofs (ZK) Instead of Pedersen Commitments on ICP

Currently, our system relies on Pedersen commitments to verify values in a privacy-preserving manner. However, a potential upgrade involves replacing Pedersen commitments with Zero-Knowledge Proofs (ZKPs) on the Internet Computer Protocol (ICP). This transition will offer several benefits:

  • Enhanced Privacy: ZKPs provide stronger privacy guarantees compared to Pedersen commitments.

  • Efficient Verification: Instead of revealing any data, ZKPs allow efficient verification of additions and other operations.

  • Partial Fault Tolerance: Implementing ZKPs can help make the system resilient to partial failures, ensuring computations remain valid even if some nodes fail.

2. Storing the Model Key and Model in a Merkle Tree Format

Currently, storing the model key and model parameters requires O(n) complexity. To optimize this, we propose storing them in a Merkle Tree structure, reducing complexity to O(log n). Benefits of this approach include:

  • Scalability: A Merkle Tree structure allows efficient lookups and updates.

  • Security: Cryptographic proofs can be used to verify integrity without revealing the entire model.

  • Efficiency: Reducing storage complexity leads to faster verification and retrieval processes.

3. Deploying the Backend for General Usability

To make the system widely accessible, a dedicated backend deployment is planned. This will involve:

  • API Development: Creating RESTful or GraphQL APIs to interact with the system.

  • Scalability Considerations: Ensuring the backend can handle multiple requests efficiently.

  • User Interface: Developing a frontend interface for seamless user interaction.

Conclusion

These future enhancements will significantly improve the security, efficiency, and usability of the system. By integrating ZKPs, Merkle Trees, and a robust backend, we aim to create a scalable, fault-tolerant, and user-friendly solution

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