Zero-Knowledge Proof of Training Secures Decentralized Federated Learning Consensus
ZKPoT, a new zk-SNARK-based primitive, validates decentralized AI model contributions without revealing sensitive training data or parameters.
Verkle Trees: Bandwidth-Efficient Authenticated Data Structures for Scalable Blockchains
Verkle Trees introduce vector commitments into Merkle-like structures, drastically reducing proof sizes for efficient blockchain state verification and enabling scalable stateless clients.
Scalable Zero-Knowledge Proofs Enhance Blockchain Hashing Verification
This research introduces a novel methodology leveraging Plonky2 to achieve efficient, scalable zero-knowledge proofs for cryptographic hashing, critical for blockchain integrity.
Distributed SNARKs Achieve Scalable Proof Generation with Novel Folding Schemes
A new distributed SNARK system leverages folding schemes to drastically accelerate proof generation for large circuits, enhancing blockchain scalability.
Adaptive Tree Restructuring Enhances Blockchain Scalability and Efficiency
This research introduces adaptive Merkle and Verkle tree restructuring, fundamentally optimizing blockchain data structures for improved scalability and reduced verification overhead.
