[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection

Z Yang, X Liu, T Li, D Wu, J Wang, Y Zhao, H Han - Computers & Security, 2022 - Elsevier
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …

Artificial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities

A Bécue, I Praça, J Gama - Artificial Intelligence Review, 2021 - Springer
This survey paper discusses opportunities and threats of using artificial intelligence (AI)
technology in the manufacturing sector with consideration for offensive and defensive uses …

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 …

Deep learning approach for intelligent intrusion detection system

R Vinayakumar, M Alazab, KP Soman… - Ieee …, 2019 - ieeexplore.ieee.org
Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

A scheme for generating a dataset for anomalous activity detection in iot networks

I Ullah, QH Mahmoud - Canadian conference on artificial intelligence, 2020 - Springer
The exponential growth of the Internet of Things (IoT) devices provides a large attack surface
for intruders to launch more destructive cyber-attacks. The intruder aimed to exhaust the …

A review of tabular data synthesis using GANs on an IDS dataset

S Bourou, A El Saer, TH Velivassaki, A Voulkidis… - Information, 2021 - mdpi.com
Recent technological innovations along with the vast amount of available data worldwide
have led to the rise of cyberattacks against network systems. Intrusion Detection Systems …

Shallow and deep networks intrusion detection system: A taxonomy and survey

E Hodo, X Bellekens, A Hamilton, C Tachtatzis… - arxiv preprint arxiv …, 2017 - arxiv.org
Intrusion detection has attracted a considerable interest from researchers and industries.
The community, after many years of research, still faces the problem of building reliable and …

Evaluation of machine learning classifiers for mobile malware detection

FA Narudin, A Feizollah, NB Anuar, A Gani - Soft Computing, 2016 - Springer
Mobile devices have become a significant part of people's lives, leading to an increasing
number of users involved with such technology. The rising number of users invites hackers …

Collective anomaly detection based on long short-term memory recurrent neural networks

L Bontemps, VL Cao, J McDermott… - Future Data and Security …, 2016 - Springer
Intrusion detection for computer network systems is becoming one of the most critical tasks
for network administrators today. It has an important role for organizations, governments and …

Security issues in Internet of Vehicles (IoV): A comprehensive survey

H Taslimasa, S Dadkhah, ECP Neto, P **ong, S Ray… - Internet of Things, 2023 - Elsevier
Nowadays, connected vehicles have a major role in enhancing the driving experience.
Connected vehicles in the network share their knowledge with the help of the network …