This study presents a hybrid data‐driven physics model‐based framework for real‐time
monitoring in smart grids. As the power grid transitions to the use of smart grid technology …

This paper presents a data-driven and physics-based method for detection of false data
injection (FDI) in Smart Grids (SG). As the power grid transitions to the use of SG technology …

In the modern Smart Grid (SG), cyber-security is an increasingly important topic of research.
An attacker can mislead the State Estimation (SE) process through a False Data Injection …

Application of computing and communications intelligence effectively improves the quality of
monitoring and control of smart grids. However, the dependence on information technology …

False Data Injection (FDI) is one of the most dangerous attacks on cyber-physical systems
as it could lead to disastrous consequences in the operation of the power grids. In this …

Security in smart grids has been investigated by many scholars so far. Among the existing
security issues, False Data Injection (FDI) attacks in energy, computers, and communication …

The false data injection (FDI) attack cannot be detected by the traditional anomaly detection
techniques used in the energy system state estimators. In this paper, we demonstrate how …

With the rapid adoption of renewables within the conventional power grid, the need of real-
time monitoring is inevitable. State estimation algorithms play a significant role in defining …

State estimation algorithms furnish an effective approach in monitoring and control of critical
infrastructures like smart grid in real-time. Recently, false data injection attack (FDIA) has …

In a smart grid, state estimation (SE) is a very important component of energy management
system. Its main functions include system SE and detection of cyber anomalies. Recently, it …