Survey of machine learning methods for detecting false data injection attacks in power systems
Over the last decade, the number of cyber attacks targeting power systems and causing
physical and economic damages has increased rapidly. Among them, false data injection …
physical and economic damages has increased rapidly. Among them, false data injection …
Security risk modeling in smart grid critical infrastructures in the era of big data and artificial intelligence
Smart grids (SG) emerged as a response to the need to modernize the electricity grid. The
current security tools are almost perfect when it comes to identifying and preventing known …
current security tools are almost perfect when it comes to identifying and preventing known …
Deep learning based attack detection for cyber-physical system cybersecurity: A survey
With the booming of cyber attacks and cyber criminals against cyber-physical systems
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …
A hybrid deep learning model for discrimination of physical disturbance and cyber-attack detection in smart grid
K Bitirgen, ÜB Filik - International Journal of Critical Infrastructure Protection, 2023 - Elsevier
A smart grid (SG) consists of an interconnection of an electrical grid, communication, and
information networks. The rapid developments of SG technologies have resulted in complex …
information networks. The rapid developments of SG technologies have resulted in complex …
Detecting stealthy false data injection attacks in the smart grid using ensemble-based machine learning
Stealthy false data injection attacks target state estimation in energy management systems
in smart power grids to adversely affect operations of the power transmission systems. This …
in smart power grids to adversely affect operations of the power transmission systems. This …
Electric power grid resilience to cyber adversaries: State of the art
The smart electricity grids have been evolving to a more complex cyber-physical ecosystem
of infrastructures with integrated communication networks, new carbon-free sources of …
of infrastructures with integrated communication networks, new carbon-free sources of …
A secured advanced management architecture in peer-to-peer energy trading for multi-microgrid in the stochastic environment
Careful consideration of grid developments illustrates the fundamental changes in its
structure which its developments have taken place gradually for a long time. One of the most …
structure which its developments have taken place gradually for a long time. One of the most …
[HTML][HTML] Anomaly detection based on lstm and autoencoders using federated learning in smart electric grid
In smart electric grid systems, various sensors and Internet of Things (IoT) devices are used
to collect electrical data at substations. In a traditional system, a multitude of energy-related …
to collect electrical data at substations. In a traditional system, a multitude of energy-related …
[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …
reputation for not only building Machine Learning (ML) models that rely on distributed …
Smart grid security and privacy: From conventional to machine learning issues (threats and countermeasures)
Smart Grid (SG) is the revolutionised power network characterised by a bidirectional flow of
energy and information between customers and suppliers. The integration of power …
energy and information between customers and suppliers. The integration of power …