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 comprehensive survey on machine learning for networking: evolution, applications and research opportunities
Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …
that solve problems and enable automation in diverse domains. Primarily, this is due to the …
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 …
Distributed denial-of-service (DDoS) attacks and defense mechanisms in various web-enabled computing platforms: issues, challenges, and future research directions
A Singh, BB Gupta - International Journal on Semantic Web and …, 2022 - igi-global.com
The demand for Internet security has escalated in the last two decades because the rapid
proliferation in the number of Internet users has presented attackers with new detrimental …
proliferation in the number of Internet users has presented attackers with new detrimental …
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 …
significant number of techniques have been developed which are based on machine …
Intrudtree: a machine learning based cyber security intrusion detection model
Cyber security has recently received enormous attention in today's security concerns, due to
the popularity of the Internet-of-Things (IoT), the tremendous growth of computer networks …
the popularity of the Internet-of-Things (IoT), the tremendous growth of computer networks …
An effective convolutional neural network based on SMOTE and Gaussian mixture model for intrusion detection in imbalanced dataset
H Zhang, L Huang, CQ Wu, Z Li - Computer Networks, 2020 - Elsevier
Abstract Network Intrusion Detection System (NIDS) is a key security device in modern
networks to detect malicious activities. However, the problem of imbalanced class …
networks to detect malicious activities. However, the problem of imbalanced class …
Deep learning approach for SDN-enabled intrusion detection system in IoT networks
Owing to the prevalence of the Internet of things (IoT) devices connected to the Internet, the
number of IoT-based attacks has been growing yearly. The existing solutions may not …
number of IoT-based attacks has been growing yearly. The existing solutions may not …
Intrusion detection based on machine learning techniques in computer networks
AS Dina, D Manivannan - Internet of Things, 2021 - Elsevier
Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
CANN: An intrusion detection system based on combining cluster centers and nearest neighbors
WC Lin, SW Ke, CF Tsai - Knowledge-based systems, 2015 - Elsevier
The aim of an intrusion detection systems (IDS) is to detect various types of malicious
network traffic and computer usage, which cannot be detected by a conventional firewall …
network traffic and computer usage, which cannot be detected by a conventional firewall …