[PDF][PDF] The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review
People in the modern era spend most of their lives in virtual environments that offer a range
of public and private services and social platforms. Therefore, these environments need to …
of public and private services and social platforms. Therefore, these environments need to …
Intrusion detection system for large-scale IoT NetFlow networks using machine learning with modified Arithmetic Optimization Algorithm
With the rapid expansion of Internet of Things (IoT) networks, the need for robust security
measures to detect and report potential threats is becoming more urgent. In this paper, we …
measures to detect and report potential threats is becoming more urgent. In this paper, we …
[HTML][HTML] Classification and explanation for intrusion detection system based on ensemble trees and SHAP method
In recent years, many methods for intrusion detection systems (IDS) have been designed
and developed in the research community, which have achieved a perfect detection rate …
and developed in the research community, which have achieved a perfect detection rate …
A lightweight IoT intrusion detection model based on improved BERT-of-Theseus
Z Wang, J Li, S Yang, X Luo, D Li… - Expert Systems with …, 2024 - Elsevier
The proliferation of Internet of Things (IoT) technology has resulted in an increase in security
vulnerabilities associated with the interconnectivity of IoT devices. As a result, there is a …
vulnerabilities associated with the interconnectivity of IoT devices. As a result, there is a …
[HTML][HTML] An ensemble tree-based model for intrusion detection in industrial internet of things networks
With less human involvement, the Industrial Internet of Things (IIoT) connects billions of
heterogeneous and self-organized smart sensors and devices. Recently, IIoT-based …
heterogeneous and self-organized smart sensors and devices. Recently, IIoT-based …
[HTML][HTML] A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Abstract The Internet of Things (IoT) is extensively used in modern-day life, such as in smart
homes, intelligent transportation, etc. However, the present security measures cannot fully …
homes, intelligent transportation, etc. However, the present security measures cannot fully …
[HTML][HTML] Malicious traffic detection in multi-environment networks using novel S-DATE and PSO-D-SEM approaches
The rapid advancement of network architectures, protocols, and tools poses significant
challenges to network security, especially due to the use of AI-based tools by cybercriminals …
challenges to network security, especially due to the use of AI-based tools by cybercriminals …
[HTML][HTML] Examining the suitability of NetFlow features in detecting IoT network intrusions
The past few years have witnessed a substantial increase in cyberattacks on Internet of
Things (IoT) devices and their networks. Such attacks pose a significant threat to …
Things (IoT) devices and their networks. Such attacks pose a significant threat to …
[HTML][HTML] Application of machine learning algorithms for the validation of a new CoAP-IoT anomaly detection dataset
L Vigoya, A Pardal, D Fernandez, V Carneiro - Applied Sciences, 2023 - mdpi.com
With the rise in smart devices, the Internet of Things (IoT) has been established as one of the
preferred emerging platforms to fulfil their need for simple interconnections. The use of …
preferred emerging platforms to fulfil their need for simple interconnections. The use of …
[HTML][HTML] IoT dataset validation using machine learning techniques for traffic anomaly detection
With advancements in engineering and science, the application of smart systems is
increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT …
increasing, generating a faster growth of the IoT network traffic. The limitations due to IoT …