Representation learning-based network intrusion detection system by capturing explicit and implicit feature interactions

W Wang, S Jian, Y Tan, Q Wu, C Huang - Computers & Security, 2022 - Elsevier
Network intrusion detection system is an important cyber defence tool to protect a system
from illegal attacks. Building an effective network intrusion detection system that makes good …

MEMBER: A multi-task learning model with hybrid deep features for network intrusion detection

J Lan, X Liu, B Li, J Sun, B Li, J Zhao - Computers & Security, 2022 - Elsevier
With the continuous occurrence of cybersecurity incidents, network intrusion detection has
become one of the most critical issues in cyber ecosystems. Although previous machine …

Weight embedding autoencoder as feature representation learning in an intrusion detection systems

M Mulyanto, JS Leu, M Faisal, W Yunanto - Computers and Electrical …, 2023 - Elsevier
The increasing need for safe internet access that withstands against various malicious
attacks has gained much attention, especially in this abundant information age. Network …

ID-RDRL: a deep reinforcement learning-based feature selection intrusion detection model

K Ren, Y Zeng, Z Cao, Y Zhang - Scientific reports, 2022 - nature.com
Network assaults pose significant security concerns to network services; hence, new
technical solutions must be used to enhance the efficacy of intrusion detection systems …

[HTML][HTML] IDS-INT: Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

F Ullah, S Ullah, G Srivastava, JCW Lin - Digital Communications and …, 2024 - Elsevier
A network intrusion detection system is critical for cyber security against illegitimate attacks.
In terms of feature perspectives, network traffic may include a variety of elements such as …

Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM

A Binbusayyis, T Vaiyapuri - Applied Intelligence, 2021 - Springer
With the rapid advancement in network technologies, the need for cybersecurity has gained
increasing momentum in recent years. As a primary defense mechanism, an intrusion …

Network intrusion detection combined hybrid sampling with deep hierarchical network

K Jiang, W Wang, A Wang, H Wu - IEEE access, 2020 - ieeexplore.ieee.org
Intrusion detection system (IDS) plays an important role in network security by discovering
and preventing malicious activities. Due to the complex and time-varying network …

Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system

V Ravi, R Chaganti, M Alazab - Computers and Electrical Engineering, 2022 - Elsevier
This work proposes an end-to-end model for network attack detection and network attack
classification using deep learning-based recurrent models. The proposed model extracts the …

Ensemble classification for intrusion detection via feature extraction based on deep Learning

M Yousefnezhad, J Hamidzadeh, M Aliannejadi - Soft Computing, 2021 - Springer
An intrusion detection system is a security system that aims to detect sabotage and
intrusions on networks to inform experts of the attack and abuse of the network. Different …

EFS‐DNN: An Ensemble Feature Selection‐Based Deep Learning Approach to Network Intrusion Detection System

Z Wang, J Liu, L Sun - Security and Communication Networks, 2022 - Wiley Online Library
In recent years, the scale of networks has substantially evolved due to the rapid
development of infrastructures in real networks. Under the circumstances, intrusion detection …