Publishing neural networks in drug discovery might compromise training data privacy

Publishing neural networks in drug discovery might compromise training data privacy

Abstract This study investigates the risks of exposing confidential chemical structures when machine learning models trained on these structures are made publicly available. We use membership inference attacks, a common method to assess privacy that is largely unexplored in the context of drug disco...

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Bibliographic Details
Main Authors: Fabian P. Krüger, Johan Östman, Lewis Mervin, Igor V. Tetko, Ola Engkvist
Format: Article
Language:English
Published: BMC 2025-03-01
Series:Journal of Cheminformatics
Subjects:
Membership inference attack
Privacy
Drug discovery
Cheminformatics
QSAR
Machine learning
Online Access:https://doi.org/10.1186/s13321-025-00982-w
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https://doi.org/10.1186/s13321-025-00982-w

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