A comprehensive review of cyber-attacks and defense mechanisms for improving security in smart grid energy systems: Past, present and future
Due to the advancement in communication networks, metering and smart control systems,
as well as the prevalent use of Internet-based structures, new forms of power systems have …
as well as the prevalent use of Internet-based structures, new forms of power systems have …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
A survey on the detection algorithms for false data injection attacks in smart grids
Cyber-physical attacks are the main substantial threats facing the utilization and
development of the various smart grid technologies. Among these attacks, false data …
development of the various smart grid technologies. Among these attacks, false data …
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
Distributed control and communication strategies in networked microgrids
Networked microgrids (NMGs) provide a promising solution for accommodating various
distributed energy resources (DERs) and enhancing the system performance in terms of …
distributed energy resources (DERs) and enhancing the system performance in terms of …
A survey on attack detection, estimation and control of industrial cyber–physical systems
D Zhang, QG Wang, G Feng, Y Shi, AV Vasilakos - ISA transactions, 2021 - Elsevier
Cyber–physical systems (CPSs) are complex systems that involve technologies such as
control, communication, and computing. Nowadays, CPSs have a wide range of applications …
control, communication, and computing. Nowadays, CPSs have a wide range of applications …
Application of big data and machine learning in smart grid, and associated security concerns: A review
This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …
learning in the electrical power grid introduced through the emergence of the next …
Smart grid architecture model for control, optimization and data analytics of future power networks with more renewable energy
This paper describes a generic methodology to develop mathematical and computational
models of different components of the smart grid architecture model (SGAM). The SGAM …
models of different components of the smart grid architecture model (SGAM). The SGAM …
Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …
interconnected devices, allowing the use of various smart applications. The enormous …
Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for CPS
Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …