most citedCocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis

5 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023★ 1 cited

Information Flow Control in Machine Learning through Modular Model Architecture

Trishita Tiwari, Suchin Gururangan, Chuan Guo +7

In today's machine learning (ML) models, any part of the training data can affect the model output. This lack of control for information flow from training data to model output is…

cs.CR2023★ 1 cited

GPU-based Private Information Retrieval for On-Device Machine Learning Inference

Maximilian Lam, Jeff Johnson, Wenjie Xiong +11

On-device machine learning (ML) inference can enable the use of private user data on user devices without revealing them to remote servers. However, a pure on-device solution to pr…

cs.CE2022★ 5 cited

Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems

Hanieh Hashemi, Wenjie Xiong, Liu Ke +4

Online personalized recommendation services are generally hosted in the cloud where users query the cloud-based model to receive recommended input such as merchandise of interest o…

cs.CR2022★ 1 cited

MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention

Wenxuan Zeng, Meng Li, Wenjie Xiong +5

Secure multi-party computation (MPC) enables computation directly on encrypted data and protects both data and model privacy in deep learning inference. However, existing neural ne…

cs.LG2022★ 5 cited

Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis

Sanjay Kariyappa, Chuan Guo, Kiwan Maeng +4

Federated learning (FL) aims to perform privacy-preserving machine learning on distributed data held by multiple data owners. To this end, FL requires the data owners to perform tr…