research
∙
04/07/2023
Does Prompt-Tuning Language Model Ensure Privacy?
Prompt-tuning has received attention as an efficient tuning method in th...
share
research
∙
01/18/2023
Label Inference Attack against Split Learning under Regression Setting
As a crucial building block in vertical Federated Learning (vFL), Split ...
research
∙
07/18/2022
On Fair Classification with Mostly Private Sensitive Attributes
Machine learning models have demonstrated promising performance in many ...
research
∙
07/09/2021
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems
Widely deployed deep neural network (DNN) models have been proven to be ...
research
∙
02/07/2021
Privacy-preserving Cloud-based DNN Inference
Deep learning as a service (DLaaS) has been intensively studied to facil...
research
∙
09/20/2020
R^2DP: A Universal and Automated Approach to Optimizing the Randomization Mechanisms of Differential Privacy for Utility Metrics with No Known Optimal Distributions
Differential privacy (DP) has emerged as a de facto standard privacy not...
research
∙
04/25/2020
Privacy Preserving Distributed Energy Trading
The smart grid incentivizes distributed agents with local generation (e....
research
∙
09/18/2019
VideoDP: A Universal Platform for Video Analytics with Differential Privacy
Massive amounts of video data are ubiquitously generated in personal dev...
research
∙
11/01/2017