Power systems are accelerating towards the transition to cyber-physical power systems
(CPPS). Such CPPS include myriads of sensors that generate huge amounts of data. The …

False data injection attacks (FDIA) against power system state estimation have been well
studied due to its potential threat to real-time energy management. However, the existing …

Data poisoning attack is a well-known attack against machine learning models, where
malicious attackers contaminate the training data to manipulate critical models and …

Smart grid (SG) is a complex cyber-physical system that utilizes modern cyber and physical
equipment to run at an optimal operating point. Cyberattacks are the principal threats …

The objective of this work is to investigate the evolution of the application of ma-chine
learning (ML) in the area of smart grids. It presents an overview of research that used ML in …

Addressing the challenges of microgrid control in the face of load variations and the
proliferation of renewable energy sources is critical. Additionally, the vulnerability of …

The rapid development of technology in the past decades created a society heavily
dependent on electricity, where even short disturbances in the power supply can result in …

This paper is concerned with the reliable operation of cyber‐physical systems under false
data injection attacks. First of all, a robust adaptive sliding mode observer is designed to …

The rapid expansion of information networks has amplified vulnerabilities in cyberspace,
particularly within the power grid and communication layers of smart grid systems …

Cyber-physical (CP) attacks are the principal dangers confronting the usage and
advancement of the contemporary smart-grid (SG) system. Advancement of SG has added a …