An efficient intrusion detection method based on dynamic autoencoder

R Zhao, J Yin, Z Xue, G Gui, B Adebisi… - IEEE Wireless …, 2021 - ieeexplore.ieee.org
The proliferation of wireless sensor networks (WSNs) and their applications has attracted
remarkable growth in unsolicited intrusions and security threats, which disrupt the normal …

An intelligent and efficient network intrusion detection system using deep learning

M Imran, N Haider, M Shoaib, I Razzak - Computers and Electrical …, 2022 - Elsevier
With continuously escalating threats and attacks, accurate and timely intrusion detection in
communication networks is challenging. Many approaches have already been proposed …

RANet: Network intrusion detection with group-gating convolutional neural network

X Zhang, F Yang, Y Hu, Z Tian, W Liu, Y Li… - Journal of Network and …, 2022 - Elsevier
With the rapid increase of human activities in cyberspace, various network intrusions are
tended to be frequent and hidden. Network intrusion detection (NID) has attracted more and …

Deep learning approach for intelligent intrusion detection system

R Vinayakumar, M Alazab, KP Soman… - Ieee …, 2019 - ieeexplore.ieee.org
Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

A network intrusion detection method based on deep multi-scale convolutional neural network

X Wang, S Yin, H Li, J Wang, L Teng - International Journal of Wireless …, 2020 - Springer
Network intrusion detection (NID) is an important method for network system administrators
to detect various security holes. The performance of traditional NID methods can be affected …

[PDF][PDF] A Deep Learning Approach to Network Intrusion Detection Using Deep Autoencoder.

S Moraboena, G Ketepalli, P Ragam - Rev. d'Intelligence Artif., 2020 - academia.edu
Accepted: 25 July 2020 The security of computer networks is critical for network intrusion
detection systems (NIDS). However, concerns exist about the suitability and sustainable …

Real-time intrusion detection in wireless network: A deep learning-based intelligent mechanism

L Yang, J Li, L Yin, Z Sun, Y Zhao, Z Li - Ieee Access, 2020 - ieeexplore.ieee.org
With the development of the wireless network techniques, the number of cyber-attack
increases significantly, which has seriously threat the security of Wireless Local Area …

DFE: efficient IoT network intrusion detection using deep feature extraction

A Basati, MM Faghih - Neural Computing and Applications, 2022 - Springer
In recent years, the Internet of Things (IoT) has received a lot of attention. It has been used in
many applications such as the control industry, industrial plants, and medicine. In this …

[HTML][HTML] A resource allocation deep active learning based on load balancer for network intrusion detection in SDN sensors

U Ahmed, JCW Lin, G Srivastava - Computer Communications, 2022 - Elsevier
Dynamic traffic in a software-defined network (SDN) causes explosive data to flow from one
system to another. The explosive data affects the functionality of system parameters, network …

LuNET: a deep neural network for network intrusion detection

P Wu, H Guo - 2019 IEEE symposium series on computational …, 2019 - ieeexplore.ieee.org
Network attack is a significant security issue for modern society. From small mobile devices
to large cloud platforms, almost all computing products, used in our daily life, are networked …