7 citations · 13 across the 6 of their papers we have counts for
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cs.CR2022★ 7 cited
SCOTCH: An Efficient Secure Computation Framework for Secure Aggregation
Yash More, Prashanthi Ramachandran, Priyam Panda +3
Federated learning enables multiple data owners to jointly train a machine learning model without revealing their private datasets. However, a malicious aggregation server might us…
cs.CR2022★ 2 cited
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
Arup Mondal, Harpreet Virk, Debayan Gupta
Federated Learning (FL) enables multiple parties to distributively train a ML model without revealing their private datasets. However, it assumes trust in the centralized aggregato…