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SVFGNN: A privacy-preserving vertical federated graph neural network model training framework based on split learning

Published Online: 2023-12-01

Published Print: 2024-01

Authors

Liu, Yanjun

Li, Hongwei

Hao, Meng
Funding

Funding for this research was provided by:

the National Key R&D Program of China (2022YFB3103500, 2022YFB3103500, 2022YFB3103500)

the Key-Area Research and Development Program of Guangdong Province (2020B0101360001, 2020B0101360001, 2020B0101360001)

the National Natural Science Foundation of China (62020106013 and 61972454, 62020106013 and 61972454, 62020106013 and 61972454)

the Fundamental Research Funds for Chinese Central Universities (ZYGX2020ZB027, ZYGX2020ZB027, ZYGX2020ZB027)
License Information

Text and Data Mining valid from 2023-12-01

Version of Record valid from 2023-12-01
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Article History

Received: 12 July 2023

Accepted: 31 October 2023

First Online: 1 December 2023

Declarations

:

: This article does not involve ethical issues (Not applicable).

: I have read and understood the publishing policy, and submit this manuscript in accordance with this policy.

: The authors declare no competing interests.

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