2 citations · 5 across the 5 of their papers we have counts for
Showing cs.CRShow all
2 papers · 1 filter
cs.CR2025
LATTEO: A Framework to Support Learning Asynchronously Tempered with Trusted Execution and Obfuscation
Abhinav Kumar, George Torres, Noah Guzinski +6
The privacy vulnerabilities of the federated learning (FL) paradigm, primarily caused by gradient leakage, have prompted the development of various defensive measures. Nonetheless,…
cs.CR2023★ 1 cited
A Generative Framework for Low-Cost Result Validation of Machine Learning-as-a-Service Inference
Abhinav Kumar, Miguel A. Guirao Aguilera, Reza Tourani +1
The growing popularity of Machine Learning (ML) has led to its deployment in various sensitive domains, which has resulted in significant research focused on ML security and privac…