[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions

R Kaur, D Gabrijelčič, T Klobučar - Information Fusion, 2023 - Elsevier
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …

Machine learning for anomaly detection: A systematic review

AB Nassif, MA Talib, Q Nasir, FM Dakalbab - Ieee Access, 2021 - ieeexplore.ieee.org
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

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 …

Machine learning-based network vulnerability analysis of industrial Internet of Things

M Zolanvari, MA Teixeira, L Gupta… - IEEE internet of things …, 2019 - ieeexplore.ieee.org
It is critical to secure the Industrial Internet of Things (IIoT) devices because of potentially
devastating consequences in case of an attack. Machine learning (ML) and big data …

A review of machine learning approaches to power system security and stability

OA Alimi, K Ouahada, AM Abu-Mahfouz - IEEE Access, 2020 - ieeexplore.ieee.org
Increasing use of renewable energy sources, liberalized energy markets and most
importantly, the integrations of various monitoring, measuring and communication …

A deep learning approach for intrusion detection in Internet of Things using focal loss function

AS Dina, AB Siddique, D Manivannan - Internet of Things, 2023 - Elsevier
Abstract Internet of Things (IoT) is likely to revolutionize healthcare, energy, education,
transportation, manufacturing, military, agriculture, and other industries. However, for the …

Host-based IDS: A review and open issues of an anomaly detection system in IoT

I Martins, JS Resende, PR Sousa, S Silva… - Future Generation …, 2022 - Elsevier
Abstract The Internet of Things (IoT) envisions a smart environment powered by connectivity
and heterogeneity where ensuring reliable services and communications across multiple …

Intelligent approaches toward intrusion detection systems for Industrial Internet of Things: A systematic comprehensive review

M Nuaimi, LC Fourati, BB Hamed - Journal of Network and Computer …, 2023 - Elsevier
Recently years, we have seen the exponential upgrowth of the Industrial Internet of Things
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …

[HTML][HTML] Adversarial attacks on machine learning cybersecurity defences in industrial control systems

E Anthi, L Williams, M Rhode, P Burnap… - Journal of Information …, 2021 - Elsevier
The proliferation and application of machine learning-based Intrusion Detection Systems
(IDS) have allowed for more flexibility and efficiency in the automated detection of cyber …

An ensemble of deep recurrent neural networks for detecting IoT cyber attacks using network traffic

M Saharkhizan, A Azmoodeh… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Internet-of-Things (IoT) devices and systems will be increasingly targeted by cybercriminals
(including nation state-sponsored or affiliated threat actors) as they become an integral part …