[HTML][HTML] Deep learning-based intrusion detection approach for securing industrial Internet of Things

S Soliman, W Oudah, A Aljuhani - Alexandria Engineering Journal, 2023 - Elsevier
The widespread deployment of the Internet of Things (IoT) into critical sectors such as
industrial and manufacturing has resulted in the Industrial Internet of Things (IIoT). The IIoT …

[HTML][HTML] Man-in-the-middle attacks in mobile ad hoc networks (MANETs): Analysis and evaluation

MA Al-Shareeda, S Manickam - Symmetry, 2022 - mdpi.com
Mobile ad hoc networks (MANETs) are being used more and more in a variety of fields,
including the environment, energy efficiency, smart transportation, intelligent agriculture, and …

A deep learning integrated blockchain framework for securing industrial IoT

A Aljuhani, P Kumar, R Alanazi… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) is a collection of interconnected smart sensors and
actuators with industrial software tools and applications. IIoT aims to enhance manufacturing …

An intelligent and explainable SAAS-based Intrusion Detection System for resource-constrained IoMT

A Aljuhani, A Alamri, P Kumar… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The Internet of Medical Things (IoMT) has revolutionized healthcare, but its vulnerabilities
demand robust security solutions, especially for resource-constrained devices. In this …

[HTML][HTML] Strength of Deep Learning-based Solutions to Secure Healthcare IoT: A Critical Review

AT Mathew, P Mani - The Open …, 2023 - openbiomedicalengineeringjournal …
Healthcare applications of IoT systems have gained huge popularity across the globe. From
personal monitoring to expert clinical diagnosis, healthcare IoT systems have shown their …

Predicting ARP spoofing with machine learning

M Usmani, M Anwar, K Farooq… - … on emerging trends …, 2022 - ieeexplore.ieee.org
Securing a network from potential attacks has become a great challenge after the advent of
sensor networks that consists of different sensors connected by wireless settings, to sense …

An investigation into the performances of the state-of-the-art machine learning approaches for various cyber-attack detection: A survey

T Ige, C Kiekintveld, A Piplai - arXiv preprint arXiv:2402.17045, 2024 - arxiv.org
To secure computers and information systems from attackers taking advantage of
vulnerabilities in the system to commit cybercrime, several methods have been proposed for …

Man-in-the-middle attack detection using ensemble learning

K Das, R Basu, R Karmakar - 2022 13th International …, 2022 - ieeexplore.ieee.org
Cyber security is one of the most vital demands about network infrastructure and hence very
necessary to protect the information sent and received during data transmission against …

Eavesdropping Attack Detection in UAVs using Ensemble Learning

K Das, C Ghosh, R Karmakar - 2023 Second International …, 2023 - ieeexplore.ieee.org
The use of Unmanned Aerial Vehicles (UAVs) is proliferated and is prone to cyber attacks.
Eavesdropping attack is an active threat to the security of an UAV as attackers intercept the …

[PDF][PDF] Man-in-the-Middle Attacks in Mobile Ad Hoc Networks (MANETs): Analysis and Evaluation. Symmetry 2022; 14: 1543

MA Al-Shareeda, S Manickam - 2022 - researchgate.net
Mobile ad hoc networks (MANETs) are being used more and more in a variety of fields,
including the environment, energy efficiency, smart transportation, intelligent agriculture, and …