We aim to develop scalable, privacy-preserving federated learning frameworks that integrate [[ZKP/ZKP Base Layer/Core Concepts/Zero-Knowledge Proofs|zero-knowledge proofs]] and [[ZKP/Research/Advanced Federated Learning/Secure Aggregation with SMPC|secure multi-party computation]] to enhance security and trust in decentralized AI training, leveraging [[Substrate]]'s [[Proof Pods in the Data Marketplace|off-chain worker]] infrastructure. See also: [[Zero-Knowledge Proofs for Model Updates]]