Główne pojęcia
Blockchain integration enhances security, fairness, and scalability in Federated Learning systems.
Streszczenie
Federated Learning (FL) ensures data privacy and confidentiality.
Challenges in FL include lack of incentives, security vulnerabilities, and single points of failure.
Blockchain integration in FL systems addresses these challenges.
Two types of decentralization architectures in BC-FL: complete and partial.
Workflow of BC-FL involves initialization, local model training, model upload, transaction broadcast, block generation, global model sharing, and new iteration training.
Reputation management in BC-FL ensures trust and reliability among clients.
Incentive mechanisms in BC-FL attract clients to participate and contribute high-quality data.
Security enhancements in BC-FL leverage blockchain's features like transparency, auditability, and immutability.
Statystyki
Blockchain-Technologie bietet mehr Sicherheit, Fairness und Skalierbarkeit in FL-Systemen.
Cytaty
"Blockchain technology is integrated into FL systems to provide stronger security, fairness, and scalability."