A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges

A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …

Survey of intrusion detection systems: techniques, datasets and challenges

A Khraisat, I Gondal, P Vamplew, J Kamruzzaman - Cybersecurity, 2019 - Springer
Cyber-attacks are becoming more sophisticated and thereby presenting increasing
challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade …

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 …

A review on machine learning and deep learning perspectives of IDS for IoT: recent updates, security issues, and challenges

A Thakkar, R Lohiya - Archives of Computational Methods in Engineering, 2021 - Springer
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as
academic field. The objective of IoT is to combine the physical environment with the cyber …

Building an efficient intrusion detection system based on feature selection and ensemble classifier

Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …

SMOTE for learning from imbalanced data: progress and challenges, marking the 15-year anniversary

A Fernández, S Garcia, F Herrera, NV Chawla - Journal of artificial …, 2018 - jair.org
The Synthetic Minority Oversampling Technique (SMOTE) preprocessing algorithm is
considered" de facto" standard in the framework of learning from imbalanced data. This is …

A detailed investigation and analysis of using machine learning techniques for intrusion detection

P Mishra, V Varadharajan… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …

Multi-dimensional feature fusion and stacking ensemble mechanism for network intrusion detection

H Zhang, JL Li, XM Liu, C Dong - Future Generation Computer Systems, 2021 - Elsevier
A robust network intrusion detection system (NIDS) plays an important role in cyberspace
security for protecting confidential systems from potential threats. In real world network, there …

A review of recent approaches on wrapper feature selection for intrusion detection

J Maldonado, MC Riff, B Neveu - Expert Systems with Applications, 2022 - Elsevier
In this paper, we present a review of recent advances in wrapper feature selection
techniques for attack detection and classification, applied in intrusion detection area. Due to …

A novel two-stage deep learning model for efficient network intrusion detection

FA Khan, A Gumaei, A Derhab, A Hussain - Ieee Access, 2019 - ieeexplore.ieee.org
The network intrusion detection system is an important tool for protecting computer networks
against threats and malicious attacks. Many techniques have recently been proposed; …