Split-n-Chain uses blockchain for privacy-preserving split learning

Researchers have introduced Split-n-Chain, a novel approach to privacy-preserving split learning that leverages blockchain for auditability. This method divides deep learning network layers across multiple distributed nodes, ensuring that data owners do not share their raw training data and that nodes only access parameters for the layers they hold. Experimental results indicate that Split-n-Chain is efficient and achieves training loss trends comparable to monolithic implementations. AI

IMPACT Enhances privacy in distributed deep learning training by securing data and model parameters.

RANK_REASON The cluster describes a new academic paper detailing a novel method for privacy-preserving machine learning. [lever_c_demoted from research: ic=1 ai=1.0]

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• alphaXiv
• arXiv
• Binanda Sengupta
• blockchain
• DagsHub
• deep learning
• federated learning
• Hugging Face
• machine learning
• Split-n-Chain

• paper
• safety

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