Network anomaly detection: methods, systems and tools
MH Bhuyan, DK Bhattacharyya… - … surveys & tutorials, 2013 - ieeexplore.ieee.org
Network anomaly detection is an important and dynamic research area. Many network
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …
intrusion detection methods and systems (NIDS) have been proposed in the literature. In this …
A holistic review of network anomaly detection systems: A comprehensive survey
N Moustafa, J Hu, J Slay - Journal of Network and Computer Applications, 2019 - Elsevier
Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in
most network defense systems for detecting and preventing potential threats. The paper …
most network defense systems for detecting and preventing potential threats. The paper …
A Comprehensive Survey on Machine Learning‐Based Intrusion Detection Systems for Secure Communication in Internet of Things
SVN Santhosh Kumar, M Selvi… - Computational …, 2023 - Wiley Online Library
The Internet of Things (IoT) is a distributed system which is made up of the connections of
smart objects (things) that can continuously sense the events in their sensing domain and …
smart objects (things) that can continuously sense the events in their sensing domain and …
A hybrid unsupervised clustering-based anomaly detection method
In recent years, machine learning-based cyber intrusion detection methods have gained
increasing popularity. The number and complexity of new attacks continue to rise; therefore …
increasing popularity. The number and complexity of new attacks continue to rise; therefore …
From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …
attacks. This holds true, as more and more organizations admit compromises on a daily …
A taxonomy of network threats and the effect of current datasets on intrusion detection systems
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 …
building secure applications, systems and networks are some of the main challenges faced …
A hybrid machine learning approach for malicious behaviour detection and recognition in cloud computing
M Rabbani, YL Wang, R Khoshkangini… - Journal of Network and …, 2020 - Elsevier
The rapid growth of new emerging computing technologies has encouraged many
organizations to outsource their data and computational requirements. Such services are …
organizations to outsource their data and computational requirements. Such services are …
Internet attacks and intrusion detection system: A review of the literature
Purpose The paper addresses various cyber threats and their effects on the internet. A
review of the literature on intrusion detection systems (IDSs) as a means of mitigating …
review of the literature on intrusion detection systems (IDSs) as a means of mitigating …
A review on machine learning approaches for network malicious behavior detection in emerging technologies
Network anomaly detection systems (NADSs) play a significant role in every network
defense system as they detect and prevent malicious activities. Therefore, this paper offers …
defense system as they detect and prevent malicious activities. Therefore, this paper offers …
MARK-ELM: application of a novel multiple kernel learning framework for improving the robustness of network intrusion detection
Detection of cyber-based attacks on computer networks continues to be a relevant and
challenging area of research. Daily reports of incidents appear in public media including …
challenging area of research. Daily reports of incidents appear in public media including …