Smart grid security and privacy: From conventional to machine learning issues (threats and countermeasures)
PH Mirzaee, M Shojafar, H Cruickshank… - IEEE access, 2022 - ieeexplore.ieee.org
Smart Grid (SG) is the revolutionised power network characterised by a bidirectional flow of
energy and information between customers and suppliers. The integration of power …
energy and information between customers and suppliers. The integration of power …
[HTML][HTML] A review on machine learning techniques for secured cyber-physical systems in smart grid networks
The smart grid (SG) is an advanced cyber-physical system (CPS) that integrates power grid
infrastructure with information and communication technologies (ICT). This integration …
infrastructure with information and communication technologies (ICT). This integration …
Security risk modeling in smart grid critical infrastructures in the era of big data and artificial intelligence
Smart grids (SG) emerged as a response to the need to modernize the electricity grid. The
current security tools are almost perfect when it comes to identifying and preventing known …
current security tools are almost perfect when it comes to identifying and preventing known …
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
Vulnerability of machine learning approaches applied in iot-based smart grid: A review
Machine learning (ML) sees an increasing prevalence of being used in the Internet of Things
(IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must be …
(IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must be …
Deep learning for cybersecurity in smart grids: Review and perspectives
Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …
significant attention in recent years. The application of artificial intelligence (AI), particularly …
Is machine learning in power systems vulnerable?
Recent advances in Machine Learning (ML) have led to its broad adoption in a series of
power system applications, ranging from meter data analytics, renewable/load/price …
power system applications, ranging from meter data analytics, renewable/load/price …
Machine learning for protection of distribution networks and power electronics-interfaced systems
Distribution network protection is becoming more sophisticated in the wake of ever-changing
landscape of power systems driven by the vast renewable energy integration mostly sited …
landscape of power systems driven by the vast renewable energy integration mostly sited …
Survey of security advances in smart grid: A data driven approach
With the integration of advanced computing and communication technologies, smart grid is
considered as the next-generation power system, which promises self healing, resilience …
considered as the next-generation power system, which promises self healing, resilience …
A review of denial of service attack and mitigation in the smart grid using reinforcement learning
I Ortega-Fernandez, F Liberati - Energies, 2023 - mdpi.com
The smart grid merges cyber-physical systems (CPS) infrastructure with information and
communication technologies (ICT) to ensure efficient power generation, smart energy …
communication technologies (ICT) to ensure efficient power generation, smart energy …