Machine learning for risk and resilience assessment in structural engineering: Progress and future trends

X Wang, RK Mazumder, B Salarieh… - Journal of Structural …, 2022 - ascelibrary.org
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

[HTML][HTML] Deep learning for intelligent demand response and smart grids: A comprehensive survey

P Boopathy, M Liyanage, N Deepa, M Velavali… - Computer Science …, 2024 - Elsevier
Electricity is one of the mandatory commodities for mankind today. To address challenges
and issues in the transmission of electricity through the traditional grid, the concepts of smart …

Cyber-physical energy systems security: Threat modeling, risk assessment, resources, metrics, and case studies

I Zografopoulos, J Ospina, X Liu, C Konstantinou - IEEE Access, 2021 - ieeexplore.ieee.org
Cyber-physical systems (CPS) are interconnected architectures that employ analog and
digital components as well as communication and computational resources for their …

Consumer, commercial, and industrial iot (in) security: Attack taxonomy and case studies

C Xenofontos, I Zografopoulos… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) devices are becoming ubiquitous in our lives, with applications
spanning from the consumer domain to commercial and industrial systems. The steep …

Attack graph model for cyber-physical power systems using hybrid deep learning

A Presekal, A Ştefanov, VS Rajkumar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Electrical power grids are vulnerable to cyber attacks, as seen in Ukraine in 2015 and 2016.
However, existing attack detection methods are limited. Most of them are based on power …

False data injection attack in smart grid cyber physical system: Issues, challenges, and future direction

AKMA Habib, MK Hasan, A Alkhayyat, S Islam… - Computers and …, 2023 - Elsevier
Smart grid integrates the physical power system infrastructure with internet-of-things-based
digital communication networks that work together for grid stability, sustainability, and …

Joint detection and localization of stealth false data injection attacks in smart grids using graph neural networks

O Boyaci, MR Narimani, KR Davis… - … on Smart Grid, 2021 - ieeexplore.ieee.org
False data injection attacks (FDIA) are a main category of cyber-attacks threatening the
security of power systems. Contrary to the detection of these attacks, less attention has been …

Contactless technologies for smart cities: big data, IoT, and cloud infrastructures

A Manimuthu, V Dharshini, I Zografopoulos… - SN computer …, 2021 - Springer
Intelligent systems are enhancing city environments and improving their overall performance
in all possible aspects. Innovations in the field of information and communication …

Cyber-resilient smart cities: Detection of malicious attacks in smart grids

M Mohammadpourfard, A Khalili, I Genc… - Sustainable Cities and …, 2021 - Elsevier
A massive challenge for future cities is being environmentally sustainable by incorporating
renewable energy resources (RES). At the same time, future smart cities need to support …

Adaptive fuzzy asynchronous control for nonhomogeneous Markov jump power systems under hybrid attacks

S Dong, M Liu - IEEE Transactions on Fuzzy Systems, 2022 - ieeexplore.ieee.org
This article investigates the adaptive fuzzy asynchronous control problem for discrete-time
nonhomogeneous Markov jump power systems under hybrid attacks. A nonhomogeneous …