NIST · ИТ · 8004e52860e89c69967e
BIT-FL: Blockchain-Enabled Incentivized And Secure Federated Learning Framework
Federated learning (FL) enables the protection of data privacy through collaborative training of a machine learning (ML) model without sharing local data. However, several common problems arise when designing FL frameworks, as they rely on a central server
NIST · ИТОфициальный источник · 2024-10-14
{
"title_en": "BIT-FL: Blockchain-Enabled Incentivized And Secure Federated Learning Framework",
"designation": "",
"series": "",
"status": "",
"date": "2024-10-14",
"date_original": "October 14, 2024",
"url": "https://www.nist.gov/publications/bit-fl-blockchain-enabled-incentivized-and-secure-federated-learning-framework",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Tao Zhang , Chenhao Ying, Fuyuan Xia, Haiming Jin, Yuan Luo, David Wei, Xinchun Yu, Yibin Xu, Xikun Jiang, Weiting Zhang, Dacheng Tao",
"abstract_excerpt_en": "Federated learning (FL) enables the protection of data privacy through collaborative training of a machine learning (ML) model without sharing local data. However, several common problems arise when designing FL frameworks, as they rely on a central server",
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{
"title_en": "BIT-FL: Blockchain-Enabled Incentivized And Secure Federated Learning Framework",
"designation": "",
"series": "",
"status": "",
"date": "2024-10-14",
"date_original": "October 14, 2024",
"url": "https://www.nist.gov/publications/bit-fl-blockchain-enabled-incentivized-and-secure-federated-learning-framework",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Tao Zhang , Chenhao Ying, Fuyuan Xia, Haiming Jin, Yuan Luo, David Wei, Xinchun Yu, Yibin Xu, Xikun Jiang, Weiting Zhang, Dacheng Tao",
"abstract_excerpt_en": "Federated learning (FL) enables the protection of data privacy through collaborative training of a machine learning (ML) model without sharing local data. However, several common problems arise when designing FL frameworks, as they rely on a central server"
}
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