MatSwarm: trusted swarm transfer learning driven materials computation for secure big data sharing.

ABSTRACT: The rapid advancement of Industry 4.0 necessitates close collaboration among material research institutions to accelerate the development of novel materials. However, multi-institutional cooperation faces significant challenges in protecting sensitive data, leading to data silos. Additionally, the heterogeneous and non-independent and identically distributed (non-i.i.d.) nature of material data hinders model accuracy and generalization in collaborative computing. In this paper, we introduce the MatSwarm framework, built on swarm learning, which integrates federated learning with blockchain technology. MatSwarm features two key innovations: a swarm transfer learning method with a regularization term to enhance the alignment of local model parameters, and the use of Trusted Execution Environ

SUBMITTER: Wang R 

PROVIDER: S-EPMC11519480 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature