Comparative study of ML models for IIoT intrusion detection: impact of data preprocessing and balancing
This study investigates the effectiveness of six prominent machine learning models—
random forest, decision trees, K-nearest neighbor, logistic regression, support vector …
random forest, decision trees, K-nearest neighbor, logistic regression, support vector …
[HTML][HTML] A comparative assessment of machine learning algorithms in the IoT-based network intrusion detection systems
M Samantaray, RC Barik, AK Biswal - Decision Analytics Journal, 2024 - Elsevier
The rapid increase in online risks is a reflection of the exponential growth of Internet of
Things (IoT) networks. Researchers have proposed numerous intrusion detection …
Things (IoT) networks. Researchers have proposed numerous intrusion detection …
Enhancing intrusion detection in IIoT: optimized CNN model with multi-class SMOTE balancing
This work introduces an intrusion detection system (IDS) tailored for industrial internet of
things (IIoT) environments based on an optimized convolutional neural network (CNN) …
things (IIoT) environments based on an optimized convolutional neural network (CNN) …
Securing Smart Homes Using Hybrid Stacking Ensemble Deep Learning-Enabled Framework
A Moubayed, MN Injadat… - … on Electrical, Energy …, 2023 - ieeexplore.ieee.org
The added deployment of Internet-of-Things (IoT) devices in various environments has led to
people increasingly adding this technology to their homes to make them more comfortable …
people increasingly adding this technology to their homes to make them more comfortable …
Machine Learning-Based Approach for Detecting DDoS Attack in SDN
A Alnatsheh, A Alsarhan, M Aljaidi… - … on Electrical, Energy …, 2023 - ieeexplore.ieee.org
With the great widespread networking and Software-Defined Network (SDN) solutions,
software-defined networks have become the target of many different attacks and security …
software-defined networks have become the target of many different attacks and security …