Integration with Homomorphic Encryption
Combine differential privacy with homomorphic encryption to enable computations on encrypted, noisy data, adding an extra privacy layer within Substrate's runtime environment.
Enhanced Security for Federated Learning
This enhances security for federated learning. Homomorphic encryption allows computations on encrypted data, and adding noise to the outputs ensures that even if the encrypted data is compromised, the noisy results cannot be used to infer individual contributions, providing a robust defense for collaborative AI training across multiple parties coordinated through Substrate's off-chain workers.
The Proof Behind Champions
Those who compete at the edge of human precision now back the technology that defines digital truth.
Buy Zero Knowledge Proof Coin Before It Hits the Market
Join the Auction