[HTML][HTML] Electric load forecasting under False Data Injection Attacks using deep learning

A Moradzadeh, M Mohammadpourfard, C Konstantinou… - Energy Reports, 2022 - Elsevier
Precise electric load forecasting at different time horizons is an essential aspect for electricity
producers and consumers who participate in energy markets in order to maximize their …

Deep learning-based cyber resilient dynamic line rating forecasting

A Moradzadeh, M Mohammadpourfard, I Genc… - International Journal of …, 2022 - Elsevier
Increased integration of renewable energy resources into the grid may create new difficulties
for ensuring a sustainable power grid which drives electric utilities to use a number of cost …

Defending Smart Electrical Power Grids against Cyberattacks with Deep -Learning

M Moradi, Y Weng, YC Lai - PRX Energy, 2022 - APS
A key to ensuring the security of smart electrical power grids is to devise and deploy effective
defense strategies against cyberattacks. To achieve this goal, an essential task is to simulate …

Attack detection and localization in smart grid with image-based deep learning

M Mohammadpourfard, I Genc… - … for smart grids …, 2021 - ieeexplore.ieee.org
Smart grid's objective is to enable electricity and information to flow two-way while providing
effective, robust, computerized, and decentralized energy delivery. This necessitates the use …

Vulnerability analysis of distributed state estimation under joint deception attacks

H Wang, K Liu, D Han, Y Xia - Automatica, 2023 - Elsevier
This paper is concerned with the vulnerability of distributed state estimation under joint
deception attacks. We first consider that all the output measurements and state estimations …

Preserving microgrid sustainability through robust islanding detection scheme ensuring cyber-situational awareness

M Tajdinian, M Mohammadpourfard, Y Weng… - Sustainable Cities and …, 2023 - Elsevier
Along with the numerous environmental and operational benefits of renewable energy
sources (RESs) integration into modern distribution networks, maintaining system security in …

An accurate false data injection attack (FDIA) detection in renewable-rich power grids

M Mohammadpourfard, Y Weng… - 2022 10th Workshop …, 2022 - ieeexplore.ieee.org
An accurate state estimation (SE) considering increased uncertainty by the high penetration
of renewable energy systems (RESs) is more and more important to enhance situational …

Optimal Encryption Scheduling Policy Against Eavesdropping Attacks in Cyber-Physical Systems

F Tao, D Ye - IEEE Transactions on Industrial Informatics, 2024 - ieeexplore.ieee.org
This article studies the optimal encryption scheduling for remote state estimation in cyber-
physical systems (CPSs) against eavesdropping attacks. A smart sensor sends packets to a …

Data-driven Technology Applications in Planning, Demand-side Management, and Cybersecurity for Smart Household Community

D Naware, A Mitra - IEEE Transactions on Artificial Intelligence, 2024 - ieeexplore.ieee.org
The need for data-driven technologies such as artificial intelligence (AI), machine learning
(ML), and deep learning (DL) in various sectors has been soaring for over a decade. The …

Cyber-physical attack conduction and detection in decentralized power systems

M Mohammadpourfard, Y Weng, A Khalili, I Genc… - IEEE …, 2022 - ieeexplore.ieee.org
The expansion of power systems over large geographical areas renders centralized
processing inefficient. Therefore, the distributed operation is increasingly adopted. This work …