[HTML][HTML] Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets
Abstract The Internet of Things (IoT) has transformed many aspects of modern life, from
healthcare and transportation to home automation and industrial control systems. However …
healthcare and transportation to home automation and industrial control systems. However …
An intrusion detection system for edge-envisioned smart agriculture in extreme environment
The deployment of Internet of Things (IoT) systems in smart agriculture (SA) operates in
extreme environments, including wind, snowfall, flooding, landscape, and so on for …
extreme environments, including wind, snowfall, flooding, landscape, and so on for …
A two-layer fog-cloud intrusion detection model for IoT networks
S Roy, J Li, Y Bai - Internet of Things, 2022 - Elsevier
Abstract The Internet of Things (IoT) and its applications are becoming ubiquitous in our life.
However, the open deployment environment and the limited resources of IoT devices make …
However, the open deployment environment and the limited resources of IoT devices make …
A Comparative Analysis of Intrusion Detection Systems: Leveraging Classification Algorithms and Feature Selection Techniques
V Shakir, A Mohsin - Journal of Applied Science and Technology Trends, 2024 - jastt.org
With the increasing use of the Internet and its coverage of all areas of life and the increasing
amount of sensitive and confidential information on the Internet, the number of malicious …
amount of sensitive and confidential information on the Internet, the number of malicious …
[HTML][HTML] Distributed denial of service attack detection in E-government cloud via data clustering
FJ Abdullayeva - Array, 2022 - Elsevier
One of the main essential security issues of cloud computing is the detection and prevention
of network intrusions. The gaps in the network directly affect the security of the cloud as it is …
of network intrusions. The gaps in the network directly affect the security of the cloud as it is …
Deep ensemble-based efficient framework for network attack detection
Nowadays, networks play a critical role in business, education, and daily life, allowing
people to communicate via different platforms across long distances. However, such …
people to communicate via different platforms across long distances. However, such …
[HTML][HTML] Mitigation of black-box attacks on intrusion detection systems-based ml
Intrusion detection systems (IDS) are a very vital part of network security, as they can be
used to protect the network from illegal intrusions and communications. To detect malicious …
used to protect the network from illegal intrusions and communications. To detect malicious …
[PDF][PDF] A hybrid deep learning approach for intrusion detection in IoT networks
Internet of Things (IoT) devices have flocked the whole world through the Internet. With
increasing missioncritical IoT data traffic, attacks on IoT networks have also increased. Many …
increasing missioncritical IoT data traffic, attacks on IoT networks have also increased. Many …
On the use of machine learning approaches for the early classification in network intrusion detection
Current intrusion detection techniques cannot keep up with the increasing amount and
complexity of cyber attacks. In fact, most of the traffic is encrypted and does not allow to …
complexity of cyber attacks. In fact, most of the traffic is encrypted and does not allow to …
[PDF][PDF] Machine learning to improve the performance of anomaly-based network intrusion detection in big data
With the rapid growth of digital technology communications are overwhelmed by network
data traffic. The demand for the internet is growing every day in today's cyber world, raising …
data traffic. The demand for the internet is growing every day in today's cyber world, raising …