An experimental analysis of attack classification using machine learning in IoT networks

A Churcher, R Ullah, J Ahmad, S Ur Rehman… - Sensors, 2021 - mdpi.com
In recent years, there has been a massive increase in the amount of Internet of Things (IoT)
devices as well as the data generated by such devices. The participating devices in IoT …

XGB-RF: A hybrid machine learning approach for IoT intrusion detection

JA Faysal, ST Mostafa, JS Tamanna, KM Mumenin… - Telecom, 2022 - mdpi.com
In the past few years, Internet of Things (IoT) devices have evolved faster and the use of
these devices is exceedingly increasing to make our daily activities easier than ever …

BoostedEnML: Efficient technique for detecting cyberattacks in IoT systems using boosted ensemble machine learning

OD Okey, SS Maidin, P Adasme, R Lopes Rosa… - Sensors, 2022 - mdpi.com
Following the recent advances in wireless communication leading to increased Internet of
Things (IoT) systems, many security threats are currently ravaging IoT systems, causing …

Toward improved machine learning-based intrusion detection for Internet of Things traffic

S Alkadi, S Al-Ahmadi, MM Ben Ismail - Computers, 2023 - mdpi.com
The rapid development of Internet of Things (IoT) networks has revealed multiple security
issues. On the other hand, machine learning (ML) has proven its efficiency in building …

A comprehensive deep learning benchmark for IoT IDS

R Ahmad, I Alsmadi, W Alhamdani, L Tawalbeh - Computers & Security, 2022 - Elsevier
The significance of an intrusion detection system (IDS) in networks security cannot be
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …

Top-down machine learning-based architecture for cyberattacks identification and classification in IoT communication networks

Q Abu Al-Haija - Frontiers in big Data, 2022 - frontiersin.org
With the prompt revolution and emergence of smart, self-reliant, and low-power devices,
Internet of Things (IoT) has inconceivably expanded and impacted almost every real-life …

A deep learning methodology for predicting cybersecurity attacks on the internet of things

OA Alkhudaydi, M Krichen, AD Alghamdi - Information, 2023 - mdpi.com
With the increasing severity and frequency of cyberattacks, the rapid expansion of smart
objects intensifies cybersecurity threats. The vast communication traffic data between …

Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach

B Sharma, L Sharma, C Lal, S Roy - Expert Systems with Applications, 2024 - Elsevier
Abstract The Internet of Things (IoT) is currently seeing tremendous growth due to new
technologies and big data. Research in the field of IoT security is an emerging topic. IoT …

[HTML][HTML] Feature extraction for machine learning-based intrusion detection in IoT networks

M Sarhan, S Layeghy, N Moustafa, M Gallagher… - Digital Communications …, 2022 - Elsevier
A large number of network security breaches in IoT networks have demonstrated the
unreliability of current Network Intrusion Detection Systems (NIDSs). Consequently, network …

Internet of things cyber attacks detection using machine learning

J Alsamiri, K Alsubhi - International Journal of Advanced …, 2019 - search.proquest.com
Abstract The Internet of Things (IoT) combines hundreds of millions of devices which are
capable of interaction with each other with minimum user interaction. IoT is one of the fastest …