4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CR2024
Model Hijacking Attack in Federated Learning
Zheng Li, Siyuan Wu, Ruichuan Chen +6
Machine learning (ML), driven by prominent paradigms such as centralized and federated learning, has made significant progress in various critical applications ranging from autonom…
cs.DC2022★ 4 cited
SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training
Ahsan Ali, Syed Zawad, Paarijaat Aditya +3
In today's production machine learning (ML) systems, models are continuously trained, improved, and deployed. ML design and training are becoming a continuous workflow of various t…
cs.CR2021★ 3 cited
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Chengliang Zhang, Junzhe Xia, Baichen Yang +6
With the advancement of machine learning (ML) and its growing awareness, many organizations who own data but not ML expertise (data owner) would like to pool their data and collabo…