Detection of data-driven blind cyber-attacks on smart grid: A deep learning approach

D Mukherjee - Sustainable Cities and Society, 2023 - Elsevier
An immense challenge to future smart cities is providing resilience against cyber-attacks on
critical infrastructures like the smart grid. Data-driven cyber-attack strategies like the false …

Detection of cyber attacks in modern renewable integrated power sector: A matrix separation scheme

D Mukherjee - IEEE Transactions on Industry Applications, 2024 - ieeexplore.ieee.org
The rapid development in the modern power sector has led to the large-scale inclusion of
renewables and electric vehicles. State estimation (SE) algorithms in the control centre …

AC False Data Injection Attack Based on Robust Tensor Principle Component Analysis

H Yang, W Zhang, CY Chung, Z Wang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
False data injection attacks (FDIAs) represent a significant threat to power grid cybersecurity,
designed to manipulate crucial measurement data and thereby compromise the operation of …

Research and Prospect of Cyber-Attacks Prediction Technology for New Power Systems

J Liang, H Zhu, B Zhang, L Liu, X Liu… - 2023 IEEE 6th …, 2023 - ieeexplore.ieee.org
With the rapid advancement of new power systems construction and the rapid development
of cyber-attack technology, the cyber-attack has become the main threat to the safe and …

Stealthy False Data Injection Attacks against the Summation Detector in Cyber-Physical Systems

Y Liu, L Cheng, D Ye - IEEE Transactions on Industrial Cyber …, 2024 - ieeexplore.ieee.org
This article proposes an alternating false data injection attack strategy, which can bypass the
summation detector in cyber-physical systems. This attack strategy offsets the impact on …

Anomaly detection in smart grid using a trace-based graph deep learning model

S Ida Evangeline, S Darwin, P Peter Anandkumar… - Electrical …, 2024 - Springer
Electricity plays a significant role in the everyday lives of people. Researchers have long
been interested in the classification problem of electric power anomaly detection. Anomaly …

Randomised Sampling-Based False Data Injection Attacks Against Power System State Estimators

D Mukherjee - 2024 IEEE 14th International Workshop on …, 2024 - ieeexplore.ieee.org
The rapid integration of renewable energy sources and electric vehicles into the traditional
power grid introduces significant uncertainty and complexity. Accurately monitoring and …

Stealthy False Data Injection Attack Using Improved Singular Value Decomposition in Smart Grid

L Yang, C Li, C Wei, J Yang, G Qu… - … on Information and …, 2024 - ieeexplore.ieee.org
Smart grid is a crucial Cyber-Physical system and is prone to cyber-attacks. In this paper, we
propose a novel false data injection attack (FDIA) construction mechanism. Firstly, the …

Real-Time Estimation of Smart Grids: A Neural Network-Based Unscented Kalman Filter Approach

D Mukherjee, BK Sethi - 2024 IEEE Region 10 Symposium …, 2024 - ieeexplore.ieee.org
Dynamic state estimations in the control centres hold an important role in formulating the
current operating scenario of the grid while the states may fluctuate rapidly due to varying …

Load forecast anomaly detection under cyber attacks using a novel approach

A Agarwal - 2022 IEEE 4th International Conference on …, 2022 - ieeexplore.ieee.org
In order to make essential and practical choices about the demand and supply of energy,
power grid operators rely on load prediction data. Consequently, effective load forecasting is …