research
∙
05/22/2023
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables
Vertical federated learning (VFL) has recently emerged as an appealing d...
share
research
∙
02/03/2023
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Federated learning (FL) is the most popular distributed machine learning...
research
∙
10/04/2022
Shielding Federated Learning: Mitigating Byzantine Attacks with Less Constraints
Federated learning is a newly emerging distributed learning framework th...
research
∙
09/15/2022
SecSkyline: Fast Privacy-Preserving Skyline Queries over Encrypted Cloud Databases
The well-known benefits of cloud computing have spurred the popularity o...
research
∙
09/08/2022
OblivGM: Oblivious Attributed Subgraph Matching as a Cloud Service
In recent years there has been growing popularity of leveraging cloud co...
research
∙
07/19/2022
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning
Federated Learning (FL), a distributed machine learning paradigm, has be...
research
∙
07/01/2022
BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Label
Due to its powerful feature learning capability and high efficiency, dee...
research
∙
06/19/2022
Privacy-Preserving Analytics on Decentralized Social Graphs: The Case of Eigendecomposition
Analytics over social graphs allows to extract valuable knowledge and in...
research
∙
04/04/2022
Towards Privacy-Preserving and Verifiable Federated Matrix Factorization
Recent years have witnessed the rapid growth of federated learning (FL),...
research
∙
02/16/2022
Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service
Graphs are widely used to model the complex relationships among entities...
research
∙
02/04/2022
Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization
Federated learning has recently emerged as a paradigm promising the bene...
research
∙
11/22/2021
NTD: Non-Transferability Enabled Backdoor Detection
A backdoor deep learning (DL) model behaves normally upon clean inputs b...
research
∙
10/31/2021
Optimizing Secure Decision Tree Inference Outsourcing
Outsourcing decision tree inference services to the cloud is highly bene...
research
∙
10/26/2021
SEDML: Securely and Efficiently Harnessing Distributed Knowledge in Machine Learning
Training high-performing deep learning models require a rich amount of d...
research
∙
05/09/2021
RBNN: Memory-Efficient Reconfigurable Deep Binary Neural Network with IP Protection for Internet of Things
Though deep neural network models exhibit outstanding performance for va...
research
∙
04/08/2021
Can Differential Privacy Practically Protect Collaborative Deep Learning Inference for the Internet of Things?
Collaborative inference has recently emerged as an intriguing framework ...
research
∙
12/08/2020
RC-SSFL: Towards Robust and Communication-efficient Semi-supervised Federated Learning System
Federated Learning (FL) is an emerging decentralized artificial intellig...
research
∙
10/08/2020
Decamouflage: A Framework to Detect Image-Scaling Attacks on Convolutional Neural Networks
As an essential processing step in computer vision applications, image r...
research
∙
07/27/2020
FedEmail: Performance Measurement of Privacy-friendly Phishing Detection Enabled by Federated Learning
Artificial intelligence (AI) has been applied in phishing email detectio...
research
∙
07/15/2020
