Abstract: Federated learning enables participants to collaboratively train a global model through distributed training without sharing raw data. However, this distributed training is vulnerable to ...

Abstract: Recent years have witnessed a huge demand for artificial intelligence and machine learning applications in wireless edge networks to assist individuals with real-time services. Federated ...

The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...

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

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...