Machine and deep learning solutions for intrusion detection and prevention in IoTs: A survey

PLS Jayalaxmi, R Saha, G Kumar, M Conti… - IEEe Access, 2022 - ieeexplore.ieee.org
The increasing number of connected devices in the era of Internet of Thing (IoT) has also
increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent …

Intrusion detection based on machine learning techniques in computer networks

AS Dina, D Manivannan - Internet of Things, 2021 - Elsevier
Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …

A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT

FS Gharehchopogh, B Abdollahzadeh, S Barshandeh… - Internet of Things, 2023 - Elsevier
The increasing trend toward using the Internet of Things (IoT) increased the number of
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …

[PDF][PDF] Attack and anomaly detection in iot networks using machine learning techniques: A review

SH Haji, SY Ameen - Asian J. Res. Comput. Sci, 2021 - researchgate.net
ABSTRACT The Internet of Things (IoT) is one of today's most rapidly growing technologies.
It is a technology that allows billions of smart devices or objects known as" Things" to collect …

MOAEOSCA: an enhanced multi-objective hybrid artificial ecosystem-based optimization with sine cosine algorithm for feature selection in botnet detection in IoT

F Hosseini, FS Gharehchopogh, M Masdari - Multimedia Tools and …, 2023 - Springer
The number of Internet of Things (IoT) devices overgrows, and this technology dominates.
The importance of IoT security and the growing need to devise intrusion detection systems …

An Ensemble‐Based Multiclass Classifier for Intrusion Detection Using Internet of Things

D Rani, NS Gill, P Gulia… - Computational …, 2022 - Wiley Online Library
Internet of Things (IoT) is the fastest growing technology that has applications in various
domains such as healthcare, transportation. It interconnects trillions of smart devices through …

Botnet attacks classification in AMI networks with recursive feature elimination (RFE) and machine learning algorithms

O Kornyo, M Asante, R Opoku, K Owusu-Agyemang… - Computers & …, 2023 - Elsevier
Abstract STRIDE (Spoofing, Tampering, Repudiation, Information Disclosure, Escalation of
privilege) in advance metering infrastructure (AMI) and cloud computing have been …

Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0

I Niño-Adan, I Landa-Torres, E Portillo… - … Applications of Artificial …, 2022 - Elsevier
Normalisation is a preprocessing technique widely employed in Machine Learning (ML)-
based solutions for industry to equalise the features' contribution. However, few researchers …

[HTML][HTML] IoT multi-vector cyberattack detection based on machine learning algorithms: traffic features analysis, experiments, and efficiency

S Lysenko, K Bobrovnikova, V Kharchenko, O Savenko - Algorithms, 2022 - mdpi.com
Cybersecurity is a common Internet of Things security challenge. The lack of security in IoT
devices has led to a great number of devices being compromised, with threats from both …

ML techniques for attack and anomaly detection in internet of things networks

V Mahor, S Bijrothiya, R Mishra… - … Vehicles Volume 1 …, 2022 - Wiley Online Library
Summary The Internet of Things (IoT), is a fundamental driver of smart cities. It is the
champion of the global collaboration of machines/things, people, huge data, and processes …