Against Network Attacks in Renewable Power Plants: Malicious Behavior Defense for Federated Learning
X Wu, Z Jin, J Zhou, K Liu, Z Liu - Computer Networks, 2024 - Elsevier
As reducing carbon emissions can relieve environmental concerns, networks-supported
renewable power plants are being built more and more. Inevitable network attacks have …
renewable power plants are being built more and more. Inevitable network attacks have …
A Privacy-Preserving Federated Learning Scheme Against Poisoning Attacks in Smart Grid
Privacy preservation in federated learning (FL) has received considerable attention and
many approaches have been proposed. However, these approaches rendered the …
many approaches have been proposed. However, these approaches rendered the …
Fedisa: A semi-asynchronous federated learning framework for power system fault and cyberattack discrimination
With growing security and privacy concerns in the Smart Grid domain, intrusion detection on
critical energy infrastructure has become a high priority in recent years. To remedy the …
critical energy infrastructure has become a high priority in recent years. To remedy the …
Incentive edge-based federated learning for false data injection attack detection on power grid state estimation: A novel mechanism design approach
With the growing concern in security and privacy of smart grid, false data injection attack
detection on power grid state estimation now faces new challenges including unknown …
detection on power grid state estimation now faces new challenges including unknown …
Artificial Intelligence-Based Secured Power Grid Protocol for Smart City
Due to the modern power system's rapid development, more scattered smart grid
components are securely linked into the power system by encircling a wide electrical power …
components are securely linked into the power system by encircling a wide electrical power …
A game theory-based incentive mechanism for collaborative security of federated learning in energy blockchain environment
Y He, M Luo, B Wu, L Sun, Y Wu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
With the digital transformation of the energy industry, energy blockchain is playing an
important role in application areas, such as energy data sharing and distributed power …
important role in application areas, such as energy data sharing and distributed power …
Privacy-preserving honeypot-based detector in smart grid networks: A new design for quality-assurance and fair incentives federated learning framework
A Albaseer, M Abdallah - 2023 IEEE 20th Consumer …, 2023 - ieeexplore.ieee.org
Adopting honeypot defenses is a promising technology for protecting the industrial Internet
of Things (IIoT), particularly the Advanced Metering Infrastructure (AMI). The effectiveness of …
of Things (IIoT), particularly the Advanced Metering Infrastructure (AMI). The effectiveness of …
[HTML][HTML] FedDiSC: A computation-efficient federated learning framework for power systems disturbance and cyber attack discrimination
With the growing concern about the security and privacy of smart grid systems, cyberattacks
on critical power grid components, such as state estimation, have proven to be one of the top …
on critical power grid components, such as state estimation, have proven to be one of the top …
PnA: Robust Aggregation Against Poisoning Attacks to Federated Learning for Edge Intelligence
Federated learning (FL), which holds promise for use in edge intelligence applications for
smart cities, enables smart devices collaborate in training a global model by exchanging …
smart cities, enables smart devices collaborate in training a global model by exchanging …
Mitigating Cyber Anomalies in Virtual Power Plants Using Artificial-Neural-Network-Based Secondary Control with a Federated Learning-Trust Adaptation
Virtual power plants (VPPs) are susceptible to cyber anomalies due to their extensive
communication layer. FL-trust, an improved federated learning (FL) approach, has been …
communication layer. FL-trust, an improved federated learning (FL) approach, has been …