[HTML][HTML] Focal Causal Temporal Convolutional Neural Networks: Advancing IIoT Security with Efficient Detection of Rare Cyber-Attacks

M Miryahyaei, M Fartash, J Akbari Torkestani - Sensors, 2024 - mdpi.com
The Industrial Internet of Things (IIoT) deals with vast amounts of data that must be
safeguarded against tampering or theft. Identifying rare attacks and addressing data …

A comprehensive survey on intrusion detection algorithms

Y Li, Z Li, M Li - Computers and Electrical Engineering, 2025 - Elsevier
Although there are many reviews on Intrusion Detection Systems (IDS), the basic parts of
Intrusion Detection Algorithms (IDA), such as imbalanced datasets, feature engineering, and …

[PDF][PDF] Critical Review of Stack Ensemble Classifier for the Prediction of Young Adults' Voting Patterns Based on Parents' Political Affiliations.

G Elo, B Ghansah, E Kwaa-Aidoo - Informing Sci. Int. J. an Emerg …, 2024 - inform.nu
ABSTRACT Aim/Purpose This review paper aims to unveil some underlying machine-
learning classification algorithms used for political election predictions and how stack …

APSO-CNN-SE: An Adaptive Convolutional Neural Network Approach for IoT Intrusion Detection.

Y Ban, D Zhang, Q He, Q Shen - Computers, Materials & …, 2024 - search.ebscohost.com
The surge in connected devices and massive data aggregation has expanded the scale of
the Internet of Things (IoT) networks. The proliferation of unknown attacks and related risks …

A Comparison of Enhanced Ensemble Learning Techniques for Internet of Things Network Attack Detection

E Ismanto, J Al Amien, V Vitriani - MATRIK: Jurnal …, 2024 - journal.universitasbumigora.ac.id
Over the past few decades, the Internet of Things (IoT) has become increasingly significant
due to its capacity to enable low-cost device and sensor communication. Implementation …

Consensus hybrid ensemble machine learning for intrusion detection with explainable AI

U Ahmed, Z Jiangbin, S Khan, MT Sadiq - Journal of Network and …, 2025 - Elsevier
Intrusion detection systems (IDSs) are dynamic to cybersecurity because they protect
computer networks from malicious activity. IDS can benefit from machine learning; however …

A method of classifying IoT devices based on attack sensitivity

H Wang, D Guo, J Wei, J Li - Journal of Information Security and …, 2024 - Elsevier
The emergence of IoT has introduced new security concerns, particularly the detection of
large-scale network attacks initiated by compromised IoT devices. The diverse nature of IoT …

[HTML][HTML] Advanced Hybrid Transformer-CNN Deep Learning Model for Effective Intrusion Detection Systems with Class Imbalance Mitigation Using Resampling …

H Kamal, M Mashaly - Future Internet, 2024 - mdpi.com
Network and cloud environments must be fortified against a dynamic array of threats, and
intrusion detection systems (IDSs) are critical tools for identifying and thwarting hostile …

Anomaly detection in IOT edge computing using deep learning and instance-level horizontal reduction

N Abbasi, M Soltanaghaei… - The Journal of …, 2024 - Springer
The increasing number of network attacks has led to the development of intrusion detection
systems. However, these methods often face limitations such as high traffic flow data …

Cancer data analysis using competitive ensemble machine learning techniques

VD Prabha, R Rathipriya, JM Chatterjee - Health and Technology, 2024 - Springer
Purpose Cancer stands as a formidable adversary on the global stage, claiming a significant
number of lives each year. Yet, amidst this sobering reality, the importance of early detection …