The Paradigm of Privacy Confidential Computing Explained

Get confidential computing explained. Learn how hardware-enforced trusted execution environments (TEEs) fully protect ...

Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
IEEE

VPPFL: Verifiable Privacy-Preserving Federated Learning in Cloud Environment

Abstract: As a distributed machine learning paradigm, federated learning has attracted wide attention from academia and industry by enabling multiple users to jointly train models without sharing ...
IEEE

Efficient Privacy-Preserving Federated Learning With Improved Compressed Sensing

Abstract: To solve the data silos issue in distributed machine learning with privacy leakage, privacy-preserving federated learning (PPFL) has been extensively explored in both academic and industrial ...