[HTML][HTML] Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review

M Abdullahi, Y Baashar, H Alhussian, A Alwadain… - Electronics, 2022 - mdpi.com
In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0),
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …

Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions

N Moustafa, N Koroniotis, M Keshk… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research
attention in recent years, aiming to provide interpretability and confidence to the inner …

Design and development of a deep learning-based model for anomaly detection in IoT networks

I Ullah, QH Mahmoud - IEEE Access, 2021 - ieeexplore.ieee.org
The growing development of IoT (Internet of Things) devices creates a large attack surface
for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the …

Denial of service attack detection and mitigation for internet of things using looking-back-enabled machine learning techniques

A Mihoub, OB Fredj, O Cheikhrouhou, A Derhab… - Computers & Electrical …, 2022 - Elsevier
Abstract IoT (Internet of Things) systems are still facing a great number of attacks due to their
integration in several areas of life. The most-reported attacks against IoT systems are" …

Design and development of RNN anomaly detection model for IoT networks

I Ullah, QH Mahmoud - IEEE Access, 2022 - ieeexplore.ieee.org
Cybersecurity is important today because of the increasing growth of the Internet of Things
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …

Intrusion detection system for internet of things based on temporal convolution neural network and efficient feature engineering

A Derhab, A Aldweesh, AZ Emam… - … and Mobile Computing, 2020 - Wiley Online Library
In the era of the Internet of Things (IoT), connected objects produce an enormous amount of
data traffic that feed big data analytics, which could be used in discovering unseen patterns …

[HTML][HTML] smote-drnn: A deep learning algorithm for botnet detection in the internet-of-things networks

SI Popoola, B Adebisi, R Ande, M Hammoudeh… - Sensors, 2021 - mdpi.com
Nowadays, hackers take illegal advantage of distributed resources in a network of
computing devices (ie, botnet) to launch cyberattacks against the Internet of Things (IoT) …

[PDF][PDF] A survey of intrusion detection using deep learning in internet of things

AD Jasim - Iraqi Journal For Computer Science and Mathematics, 2022 - iasj.net
The use of deep learning in various models is a powerful tool in detecting Internet of Things
(IoT) attacks and identifying new types of intrusion to access a better secure network. The …

[HTML][HTML] FIDChain: Federated intrusion detection system for blockchain-enabled IoT healthcare applications

E Ashraf, NFF Areed, H Salem, EH Abdelhay, A Farouk - Healthcare, 2022 - mdpi.com
Recently, there has been considerable growth in the internet of things (IoT)-based
healthcare applications; however, they suffer from a lack of intrusion detection systems …

A review and analysis of the bot-iot dataset

JM Peterson, JL Leevy… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Machine learning is rapidly changing the cybersecu-rity landscape. The use of predictive
models to detect malicious activity and identify inscrutable attack patterns is providing levels …