[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 …
A review of tabular data synthesis using GANs on an IDS dataset
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 …
have led to the rise of cyberattacks against network systems. Intrusion Detection Systems …
An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture
The entire computing paradigm is changed due to the technological advancements in
Information and Communication Technology (ICT). Due to these advancements, various …
Information and Communication Technology (ICT). Due to these advancements, various …
“why should i trust your ids?”: An explainable deep learning framework for intrusion detection systems in internet of things networks
Z Abou El Houda, B Brik… - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
Internet of Things (IoT) is an emerging paradigm that is turning and revolutionizing
worldwide cities into smart cities. However, this emergence is accompanied with several …
worldwide cities into smart cities. However, this emergence is accompanied with several …
CNN-based network intrusion detection against denial-of-service attacks
As cyberattacks become more intelligent, it is challenging to detect advanced attacks in a
variety of fields including industry, national defense, and healthcare. Traditional intrusion …
variety of fields including industry, national defense, and healthcare. Traditional intrusion …
Robust detection for network intrusion of industrial IoT based on multi-CNN fusion
Y Li, Y Xu, Z Liu, H Hou, Y Zheng, Y Xin, Y Zhao, L Cui - Measurement, 2020 - Elsevier
A robust intrusion detection system plays a very important role in network security. In the
face of complex network data and diverse intrusion methods, traditional machine learning …
face of complex network data and diverse intrusion methods, traditional machine learning …
An explainable machine learning framework for intrusion detection systems
M Wang, K Zheng, Y Yang, X Wang - IEEE Access, 2020 - ieeexplore.ieee.org
In recent years, machine learning-based intrusion detection systems (IDSs) have proven to
be effective; especially, deep neural networks improve the detection rates of intrusion …
be effective; especially, deep neural networks improve the detection rates of intrusion …
Idsgan: Generative adversarial networks for attack generation against intrusion detection
Z Lin, Y Shi, Z Xue - Pacific-asia conference on knowledge discovery and …, 2022 - Springer
As an essential tool in security, the intrusion detection system bears the responsibility of the
defense to network attacks performed by malicious traffic. Nowadays, with the help of …
defense to network attacks performed by malicious traffic. Nowadays, with the help of …
A novel intrusion detection model for a massive network using convolutional neural networks
K Wu, Z Chen, W Li - Ieee Access, 2018 - ieeexplore.ieee.org
More and more network traffic data have brought great challenge to traditional intrusion
detection system. The detection performance is tightly related to selected features and …
detection system. The detection performance is tightly related to selected features and …
IoT DoS and DDoS attack detection using ResNet
The network attacks are increasing both in frequency and intensity with the rapid growth of
internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of …
internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of …