A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions

A Thakkar, R Lohiya - Artificial Intelligence Review, 2022 - Springer
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …

Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset

ZK Maseer, R Yusof, N Bahaman, SA Mostafa… - IEEE …, 2021 - ieeexplore.ieee.org
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …

A survey on machine learning techniques for cyber security in the last decade

K Shaukat, S Luo, V Varadharajan, IA Hameed… - IEEE …, 2020 - ieeexplore.ieee.org
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

Wrapper feature selection method based differential evolution and extreme learning machine for intrusion detection system

WL Al-Yaseen, AK Idrees, FH Almasoudy - Pattern Recognition, 2022 - Elsevier
The intrusion detection system (IDS) has gained a rapid increase of interest due to its widely
recognized potential in various security fields, however, it suffers from several challenges …

Unsupervised machine learning for networking: Techniques, applications and research challenges

M Usama, J Qadir, A Raza, H Arif, KLA Yau… - IEEE …, 2019 - ieeexplore.ieee.org
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

A machine learning security framework for iot systems

M Bagaa, T Taleb, JB Bernabe, A Skarmeta - IEEE access, 2020 - ieeexplore.ieee.org
Internet of Things security is attracting a growing attention from both academic and industry
communities. Indeed, IoT devices are prone to various security attacks varying from Denial …

Using machine learning algorithms to enhance IoT system security

H El-Sofany, SA El-Seoud, OH Karam… - Scientific Reports, 2024 - nature.com
Abstract The term “Internet of Things”(IoT) refers to a system of networked computing
devices that may work and communicate with one another without direct human intervention …

A taxonomy of network threats and the effect of current datasets on intrusion detection systems

H Hindy, D Brosset, E Bayne, AK Seeam… - IEEe …, 2020 - ieeexplore.ieee.org
As the world moves towards being increasingly dependent on computers and automation,
building secure applications, systems and networks are some of the main challenges faced …

Attack classification using feature selection techniques: a comparative study

A Thakkar, R Lohiya - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
The goal of securing a network is to protect the information flowing through the network and
to ensure the security of intellectual as well as sensitive data for the underlying application …

A taxonomy of machine-learning-based intrusion detection systems for the internet of things: A survey

A Jamalipour, S Murali - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is an emerging technology that has earned a lot of research
attention and technical revolution in recent years. Significantly, IoT connects and integrates …