Privacy-Preserving Federated Learning Based On Partial Low-Quality Data
Huiyong Wang,
Qi Wang,
Yong Ding
et al.
Abstract:Traditional machine learning requires collecting data from participants for training, which may result in malicious acquisition of privacy in participants' data. Federated learning offers a method to protect participants' data privacy by transferring the training process from a centralized server to terminal devices. However, the server may still obtain participants' privacy information through inference attacks, among other methods. Additionally, the data provided by participants varies in quality, and excess… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.