Machine learning in IoT security: Current solutions and future challenges

F Hussain, R Hussain, SA Hassan… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
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 …

Distributed control and communication strategies in networked microgrids

Q Zhou, M Shahidehpour, A Paaso… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Networked microgrids (NMGs) provide a promising solution for accommodating various
distributed energy resources (DERs) and enhancing the system performance in terms of …

Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for CPS

FO Olowononi, DB Rawat, C Liu - … Communications Surveys & …, 2020 - ieeexplore.ieee.org
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 …

Machine learning driven smart electric power systems: Current trends and new perspectives

MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …

Locational detection of the false data injection attack in a smart grid: A multilabel classification approach

S Wang, S Bi, YJA Zhang - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
State estimation is critical to the monitoring and control of smart grids. Recently, the false
data injection attack (FDIA) is emerging as a severe threat to state estimation. Conventional …

A machine-learning-based technique for false data injection attacks detection in industrial IoT

MMN Aboelwafa, KG Seddik… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
The accelerated move toward the adoption of the Industrial Internet-of-Things (IIoT)
paradigm has resulted in numerous shortcomings as far as security is concerned. One of the …

[HTML][HTML] Cyber-security of smart microgrids: A survey

F Nejabatkhah, YW Li, H Liang, R Reza Ahrabi - Energies, 2020 - mdpi.com
In this paper, the cyber-security of smart microgrids is thoroughly discussed. In smart grids,
the cyber system and physical process are tightly coupled. Due to the cyber system's …

Survey of machine learning methods for detecting false data injection attacks in power systems

A Sayghe, Y Hu, I Zografopoulos, XR Liu… - IET Smart …, 2020 - Wiley Online Library
Over the last decade, the number of cyber attacks targeting power systems and causing
physical and economic damages has increased rapidly. Among them, false data injection …

IoT vulnerability assessment for sustainable computing: threats, current solutions, and open challenges

P Anand, Y Singh, A Selwal, M Alazab, S Tanwar… - IEEE …, 2020 - ieeexplore.ieee.org
Over the last few decades, sustainable computing has been widely used in areas like social
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …

Machine learning meets communication networks: Current trends and future challenges

I Ahmad, S Shahabuddin, H Malik, E Harjula… - IEEE …, 2020 - ieeexplore.ieee.org
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …