A self-attention-based deep convolutional neural networks for IIoT networks intrusion detection

MS Alshehri, O Saidani, FS Alrayes, SF Abbasi… - IEEE …, 2024 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) comprises a variety of systems, smart devices, and an
extensive range of communication protocols. Hence, these systems face susceptibility to …

Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models

A Gueriani, H Kheddar, AC Mazari - arxiv preprint arxiv:2501.13962, 2025 - arxiv.org
The rapid expansion of the industrial Internet of things (IIoT) has introduced new challenges
in securing critical infrastructures against sophisticated cyberthreats. This study presents the …

Attention-Based Hybrid Deep Learning Model for Intrusion Detection in IIoT Networks

S Ullah, W Boulila, A Koubaa, J Ahmad - Procedia Computer Science, 2024 - Elsevier
Abstract The integration of Industrial Internet of Things (IIoT) technology into the industrial
sector has produced numerous significant advantages. However, the notable concern …

Securing Industrial IoT Networks Using Conv2D-Attention Approach with Softmax Classifier

B Bhola, A Raza, R Kumar - 2024 IEEE Space, Aerospace and …, 2024 - ieeexplore.ieee.org
In this paper, we propose Conv2D-attention based intrusion detection systems (IDS) to
secure the network in the industrial internet-of-things (IIoT). For this purpose, convolution on …

A software vulnerability intelligent detection method based on code association graph

H **e, C Li, J Jiang, Y Qin, F Lu… - … Conference on Image …, 2024 - spiedigitallibrary.org
In order to improve the accuracy of software source code vulnerability detection and reduce
the false positive rate, this paper proposes a software vulnerability intelligent detection …

[TRÍCH DẪN][C] An efficient internet of things based intrusion detection and optimization algorithm for smart networks

A TN, U ML - International Journal of Computing and Digital …, 2024 - University of Bahrain