research
∙
07/21/2023
Differentially Private Heavy Hitter Detection using Federated Analytics
In this work, we study practical heuristics to improve the performance o...
share
research
∙
12/12/2022
Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems
Online personalized recommendation services are generally hosted in the ...
research
∙
06/30/2022
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware
Privacy and security-related concerns are growing as machine learning re...
research
∙
12/26/2021
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings
Speech emotion recognition (SER) processes speech signals to detect and ...
research
∙
07/27/2021
Verifiable Coded Computing: Towards Fast, Secure and Private Distributed Machine Learning
Stragglers, Byzantine workers, and data privacy are the main bottlenecks...
research
∙
05/05/2021
Byzantine-Robust and Privacy-Preserving Framework for FedML
Federated learning has emerged as a popular paradigm for collaboratively...
research
∙
05/01/2021
Privacy and Integrity Preserving Training Using Trusted Hardware
Privacy and security-related concerns are growing as machine learning re...
research
∙
06/01/2020
DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks
Protecting the privacy of input data is of growing importance as machine...
research
∙
05/10/2019
