Zero-Knowledge Proof of Training Secures Private Federated Consensus
Research introduces ZKPoT, a zero-knowledge proof system validating federated learning model performance for consensus, eliminating privacy leaks and centralization risk.
Supervised Decentralized Identity Balances Anonymity, Revocability, and Regulatory Oversight
A novel DID framework integrates dynamic accumulators and zero-knowledge proofs to enable regulatory oversight and credential revocation without sacrificing user privacy.
Decentralized Private Vertical Federated Learning with Novel Feature Sharing Consensus
SecureVFL integrates a permissioned blockchain, a novel Proof of Feature Sharing consensus, and Replicated Secret Sharing for private, verifiable multi-party federated learning.
Proof of Feature Sharing Secures Decentralized Vertical Federated Learning
SecureVFL integrates a novel Proof of Feature Sharing consensus with replicated secret sharing on a permissioned blockchain, enabling robust, private, and efficient multi-party federated learning.
Blockchain Enhances Cloud Data Integrity and Privacy with Deduplication Auditing
This research secures cloud data with a blockchain framework, enabling private deduplication and audit without trusted intermediaries, ensuring integrity and ownership privacy.
Zero-Knowledge Proofs Enhance Blockchain Privacy and Verification Efficiency
This research introduces a novel zero-knowledge proof mechanism for blockchain, enabling confidential transaction verification while significantly improving network throughput and user privacy.
Decentralized Identity and Cryptography Reshape Digital Identity Management for Enhanced Control
Decentralized identity, powered by blockchain and cryptography, empowers individuals with self-sovereign control over their digital data, revolutionizing security and global accessibility.
