Threats, attacks and defenses to federated learning: issues, taxonomy and perspectives

P Liu, X Xu, W Wang - Cybersecurity, 2022 - Springer
Abstract Empirical attacks on Federated Learning (FL) systems indicate that FL is fraught
with numerous attack surfaces throughout the FL execution. These attacks can not only …

Review on security of federated learning and its application in healthcare

H Li, C Li, J Wang, A Yang, Z Ma, Z Zhang… - Future Generation …, 2023 - Elsevier
Artificial intelligence (AI) has led to a high rate of development in healthcare, and good
progress has been made on many complex medical problems. However, there is a lack of …

A federated feature selection algorithm based on particle swarm optimization under privacy protection

Y Hu, Y Zhang, X Gao, D Gong, X Song, Y Guo… - Knowledge-Based …, 2023 - Elsevier
Feature selection is an important preprocessing technique in the fields of data mining and
machine learning. With the promotion of privacy protection awareness, recently it becomes a …

[HTML][HTML] Data sharing in energy systems

J Wang, F Gao, Y Zhou, Q Guo, CW Tan, J Song… - Advances in Applied …, 2023 - Elsevier
Big data has been advocated as a dominant driving force to unleash the great waves of the
next-generation industrial revolution. While the ever-increasing proliferation of …

Vulnerability of machine learning approaches applied in iot-based smart grid: A review

Z Zhang, M Liu, M Sun, R Deng… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
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 be …

A Fully Distributed Privacy-Preserving Energy Management System for Networked Microgrid Cluster Based on Homomorphic Encryption

ZP Yuan, P Li, ZL Li, J Xia - IEEE Transactions on Smart Grid, 2023 - ieeexplore.ieee.org
The networked microgrid cluster (NMGC) integrating multiple heterogeneous microgrids is
an effective way to improve the renewable energy utilization. However, the centralized …

Preserving privacy in nested peer-to-peer energy trading in networked microgrids considering incomplete rationality

Y Xia, Q Xu, Y Huang, Y Liu, F Li - IEEE Transactions on Smart …, 2022 - ieeexplore.ieee.org
With the high penetration of renewable energy resources, energy prosumers and microgrids
can trade energy directly with each other in a hierarchical way. This paper develops a …

Data-driven aggregation of thermal dynamics within building virtual power plants

X Cui, S Liu, G Ruan, Y Wang - Applied Energy, 2024 - Elsevier
Virtual power plants (VPPs) possess the capability to aggregate flexible resources to provide
grid services in the distributed network operation. The potential for flexibility utilization in …

A privacy-preserving blockchain-based method to optimize energy trading

J Ping, Z Yan, S Chen - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
It is always desired for optimizing energy trading to disable manipulation and preserve
individual privacy. These two features become increasingly appealing for an energy market …

Privacy-preserving household characteristic identification with federated learning method

J Lin, J Ma, J Zhu - IEEE Transactions on Smart Grid, 2021 - ieeexplore.ieee.org
Understanding residential household characteristics is crucial for retailers to provide
customers personalized services. Current methods infer household characteristics from …