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Adversarial machine learning for network intrusion detection systems: A comprehensive survey
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 …
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
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
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 …
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
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 …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
Machine learning for anomaly detection: A systematic review
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 …
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 …
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
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 …
between different communicating devices. The data should be communicated securely …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
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 …
industry and academia because it can be integrated with a large number of everyday …
Survey of intrusion detection systems: techniques, datasets and challenges
Cyber-attacks are becoming more sophisticated and thereby presenting increasing
challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade …
challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade …