Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review

N Mishra, S Pandya - IEEE Access, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) technology is prospering and entering every part of our lives, be it
education, home, vehicles, or healthcare. With the increase in the number of connected …

A review on machine learning and deep learning perspectives of IDS for IoT: recent updates, security issues, and challenges

A Thakkar, R Lohiya - Archives of Computational Methods in Engineering, 2021 - Springer
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as
academic field. The objective of IoT is to combine the physical environment with the cyber …

Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis

MA Ferrag, O Friha, L Maglaras, H Janicke… - IEEE Access, 2021 - ieeexplore.ieee.org
In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …

A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions

S Arisdakessian, OA Wahab, A Mourad… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …

Federated learning for intrusion detection system: Concepts, challenges and future directions

S Agrawal, S Sarkar, O Aouedi, G Yenduri… - Computer …, 2022 - Elsevier
The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …

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 …

A survey on deep learning for cybersecurity: Progress, challenges, and opportunities

M Macas, C Wu, W Fuertes - Computer Networks, 2022 - Elsevier
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …

Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications

RA Khalil, N Saeed, M Masood, YM Fard… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
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 …

6G white paper on machine learning in wireless communication networks

S Ali, W Saad, N Rajatheva, K Chang… - arXiv preprint arXiv …, 2020 - arxiv.org
The focus of this white paper is on machine learning (ML) in wireless communications. 6G
wireless communication networks will be the backbone of the digital transformation of …

Deep learning in IoT intrusion detection

S Tsimenidis, T Lagkas, K Rantos - Journal of network and systems …, 2022 - Springer
Abstract The Internet of Things (IoT) is the new paradigm of our times, where smart devices
and sensors from across the globe are interconnected in a global grid, and distributed …