Adversarial machine learning for network intrusion detection systems: A comprehensive survey

K He, DD Kim, MR Asghar - IEEE Communications Surveys & …, 2023 - ieeexplore.ieee.org
Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …

[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 …

Predictive analytics and machine learning for real-time supply chain risk mitigation and agility

A Aljohani - Sustainability, 2023 - mdpi.com
Supply chain agility has become a key success factor for businesses trying to handle
upheavals and uncertainty in today's quickly changing business environment. Proactive risk …

Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system

MHL Louk, BA Tama - Expert Systems with Applications, 2023 - Elsevier
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …

Machine learning for anomaly detection: A systematic review

AB Nassif, MA Talib, Q Nasir, FM Dakalbab - Ieee Access, 2021 - ieeexplore.ieee.org
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

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 …

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 …

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 …

Anomaly detection in blockchain networks: A comprehensive survey

MU Hassan, MH Rehmani… - … Communications Surveys & …, 2022 - ieeexplore.ieee.org
Over the past decade, blockchain technology has attracted a huge attention from both
industry and academia because it can be integrated with a large number of everyday …

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 …