Utility–Privacy Trade-Off in Distributed Machine Learning Systems
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DOI: 10.3390/e24091299
Abstract: In distributed machine learning (DML), though clients’ data are not directly transmitted to the server for model training, attackers can obtain the sensitive information of clients by analyzing the local gradient parameters uploaded by clients.… read more here.
Keywords: distributed machine; privacy trade; utility privacy; machine learning ... See more keywords