2 papers
math.OC2024
A Novel Privacy Enhancement Scheme with Dynamic Quantization for Federated Learning
Yifan Wang, Xianghui Cao, Shi Jin +1
Federated learning (FL) has been widely regarded as a promising paradigm for privacy preservation of raw data in machine learning. Although, the data privacy in FL is locally prote…
cs.CR2023
Vulnerability of Machine Learning Approaches Applied in IoT-based Smart Grid: A Review
Zhenyong Zhang, Mengxiang Liu, Mingyang Sun +5
Machine learning (ML) sees an increasing prevalence of being used in the internet-of-things (IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must b…