Botnet detection and mitigation model for IoT networks using federated learning
FL de Caldas Filho, SCM Soares, E Oroski… - Sensors, 2023 - mdpi.com
The Internet of Things (IoT) introduces significant security vulnerabilities, raising concerns
about cyber-attacks. Attackers exploit these vulnerabilities to launch distributed denial-of …
about cyber-attacks. Attackers exploit these vulnerabilities to launch distributed denial-of …
Agnostic CH-DT technique for SCADA network high-dimensional data-aware intrusion detection system
LAC Ahakonye, CI Nwakanma… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The pervasiveness in the Industrial Internet of Things (IIoT) due to the application of
supervisory control and data acquisition (SCADA) has led to the growth of heterogeneous …
supervisory control and data acquisition (SCADA) has led to the growth of heterogeneous …
A hybrid intrusion detection system based on feature selection and weighted stacking classifier
R Zhao, Y Mu, L Zou, X Wen - IEEE Access, 2022 - ieeexplore.ieee.org
Cyber-attacks occur more frequently with the rapid growth in the Internet. Intrusion detection
systems (IDS) have become an important part of protecting system security. There are still …
systems (IDS) have become an important part of protecting system security. There are still …
Efficient classification of enciphered SCADA network traffic in smart factory using decision tree algorithm
Vulnerability detection in Supervisory Control and Data Acquisition (SCADA) network of a
Smart Factory (SF) is a high-priority research area in the cyber-security domain. Choosing …
Smart Factory (SF) is a high-priority research area in the cyber-security domain. Choosing …
Big data-aware intrusion detection system in communication networks: a deep learning approach
One of the most important parameters that hackers have always considered is obtaining
information about the status of computer networks, such as hacking into databases and …
information about the status of computer networks, such as hacking into databases and …
Representation learning-based network intrusion detection system by capturing explicit and implicit feature interactions
Network intrusion detection system is an important cyber defence tool to protect a system
from illegal attacks. Building an effective network intrusion detection system that makes good …
from illegal attacks. Building an effective network intrusion detection system that makes good …
Transferability of machine learning models learned from public intrusion detection datasets: the CICIDS2017 case study
Intrusion detection is a primary concern in any modern computer system due to the ever-
growing number of intrusions. Machine learning represents an effective solution to detect …
growing number of intrusions. Machine learning represents an effective solution to detect …
Hybrid deep-learning model to detect botnet attacks over internet of things environments
MY Alzahrani, AM Bamhdi - Soft Computing, 2022 - Springer
In recent years, the use of the internet of things (IoT) has increased dramatically, and
cybersecurity concerns have grown in tandem. Cybersecurity has become a major …
cybersecurity concerns have grown in tandem. Cybersecurity has become a major …
Griffin: Real-time network intrusion detection system via ensemble of autoencoder in SDN
Many efforts have been devoted to the development of efficient Network Intrusion Detection
System (NIDS) using machine learning approaches in Software-defined Network (SDN) …
System (NIDS) using machine learning approaches in Software-defined Network (SDN) …
[HTML][HTML] A comprehensive review of AI based intrusion detection system
T Sowmya, EAM Anita - Measurement: Sensors, 2023 - Elsevier
In today's digital world, the tremendous amount of data poses a significant challenge to
cyber security. The complexity of cyber-attacks makes it difficult to develop efficient tools to …
cyber security. The complexity of cyber-attacks makes it difficult to develop efficient tools to …