A regularized cross-layer ladder network for intrusion detection in industrial internet of things

J Long, W Liang, KC Li, Y Wei… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As part of Big Data trends, the ubiquitous use of the Internet of Things (IoT) in the industrial
environment has generated a significant amount of network traffic. In this type of IoT …

Detection of low-frequency and multi-stage attacks in industrial internet of things

X Li, M Xu, P Vijayakumar, N Kumar… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The increasingly sophisticated cyber attacks have become a serious challenge for Industrial
Internet of Things (IIoT), which presents two new characteristics: low frequency and multi …

A deep learning approach for intrusion detection in Internet of Things using focal loss function

AS Dina, AB Siddique, D Manivannan - Internet of Things, 2023 - Elsevier
Abstract Internet of Things (IoT) is likely to revolutionize healthcare, energy, education,
transportation, manufacturing, military, agriculture, and other industries. However, for the …

Cognitive memory-guided autoencoder for effective intrusion detection in internet of things

H Lu, T Wang, X Xu, T Wang - IEEE Transactions on Industrial …, 2021 - ieeexplore.ieee.org
With the development of the Internet of Things (IoT) technology, intrusion detection has
become a key technology that provides solid protection for IoT devices from network …

[HTML][HTML] Res-TranBiLSTM: An intelligent approach for intrusion detection in the Internet of Things

S Wang, W Xu, Y Liu - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT), as the information carrier of the Internet and
telecommunications networks, is a new network technology comprising physical entities …

Collaborative learning model for cyberattack detection systems in iot industry 4.0

TV Khoa, YM Saputra, DT Hoang… - 2020 IEEE wireless …, 2020 - ieeexplore.ieee.org
Although the development of IoT Industry 4.0 has brought breakthrough achievements in
many sectors, eg, manufacturing, healthcare, and agriculture, it also raises many security …

Pelican: A deep residual network for network intrusion detection

P Wu, H Guo, N Moustafa - 2020 50th annual IEEE/IFIP …, 2020 - ieeexplore.ieee.org
One challenge for building a secure network communication environment is how to
effectively detect and prevent malicious network behaviours. The abnormal network …

HNN: a novel model to study the intrusion detection based on multi-feature correlation and temporal-spatial analysis

S Lei, C Xia, Z Li, X Li, T Wang - IEEE Transactions on Network …, 2021 - ieeexplore.ieee.org
Network intrusion poses a severe threat to the Internet. Intrusion detection methods based
on deep learning are very effective to process and analyze intrusion data. On the one hand …

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 …

[HTML][HTML] Deep learning-based intrusion detection approach for securing industrial Internet of Things

S Soliman, W Oudah, A Aljuhani - Alexandria Engineering Journal, 2023 - Elsevier
The widespread deployment of the Internet of Things (IoT) into critical sectors such as
industrial and manufacturing has resulted in the Industrial Internet of Things (IIoT). The IIoT …