Linear-Time Post-Quantum SNARKs Achieve Optimal Prover Efficiency
Brakedown introduces the first built linear-time SNARK, achieving optimal O(N) prover complexity for large computations while eliminating trusted setup.
Zero-Knowledge Proof of Training Secures Private Decentralized Federated Learning Consensus
ZKPoT introduces a zk-SNARK-based consensus mechanism that proves model accuracy without revealing private data, resolving the critical privacy-accuracy trade-off in decentralized AI.
Zero-Knowledge Proof of Training Secures Private Federated Learning Consensus
ZKPoT consensus validates machine learning contributions privately using zk-SNARKs, balancing efficiency, security, and data privacy for decentralized AI.
