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06/08/2023
FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs
This paper introduces FedMLSecurity, a benchmark that simulates adversar...
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03/21/2023
Secure Aggregation in Federated Learning is not Private: Leaking User Data at Large Scale through Model Modification
Security and privacy are important concerns in machine learning. End use...
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03/20/2023
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System
Federated Learning (FL) enables machine learning model training on distr...
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02/27/2023
Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain
We consider a project (model) owner that would like to train a model by ...
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08/03/2022
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?
Federated learning (FL) has attracted growing interest for enabling priv...
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09/29/2021
LightSecAgg: Rethinking Secure Aggregation in Federated Learning
Secure model aggregation is a key component of federated learning (FL) t...
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04/14/2021
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks
Graph Neural Network (GNN) research is rapidly growing thanks to the cap...
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12/23/2019
