[HTML][HTML] Performance of machine learning-based multi-model voting ensemble methods for network threat detection in agriculture 4.0
N Peppes, E Daskalakis, T Alexakis, E Adamopoulou… - Sensors, 2021 - mdpi.com
The upcoming agricultural revolution, known as Agriculture 4.0, integrates cutting-edge
Information and Communication Technologies in existing operations. Various cyber threats …
Information and Communication Technologies in existing operations. Various cyber threats …
Malicious traffic detection in iot and local networks using stacked ensemble classifier
Malicious traffic detection over the internet is one of the challenging areas for researchers to
protect network infrastructures from any malicious activity. Several shortcomings of a …
protect network infrastructures from any malicious activity. Several shortcomings of a …
[HTML][HTML] Cyber security for detecting distributed denial of service attacks in agriculture 4.0: Deep learning model
THH Aldhyani, H Alkahtani - Mathematics, 2023 - mdpi.com
Attackers are increasingly targeting Internet of Things (IoT) networks, which connect
industrial devices to the Internet. To construct network intrusion detection systems (NIDSs) …
industrial devices to the Internet. To construct network intrusion detection systems (NIDSs) …
[HTML][HTML] Design of efficient based artificial intelligence approaches for sustainable of cyber security in smart industrial control system
A Alzahrani, THH Aldhyani - Sustainability, 2023 - mdpi.com
Online food security and industrial environments and sustainability-related industries are
highly confidential and in urgent need for network traffic analysis to attain proper security …
highly confidential and in urgent need for network traffic analysis to attain proper security …
[HTML][HTML] AI-enabled traffic control prioritization in software-defined IoT networks for smart agriculture
Smart agricultural systems have received a great deal of interest in recent years because of
their potential for improving the efficiency and productivity of farming practices. These …
their potential for improving the efficiency and productivity of farming practices. These …
[HTML][HTML] Deep learning-based intrusion detection for distributed denial of service attack in agriculture 4.0
Smart Agriculture or Agricultural Internet of things, consists of integrating advanced
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
Voting-based ensemble learning approach for cyber attacks detection in Industrial Internet of Things
Abstract The Industrial Internet of Things (IIoT) is a fast developing interconnection of smart
technologies that have revolutionised the way the industries work by combining sensors and …
technologies that have revolutionised the way the industries work by combining sensors and …
Mitigating cyber threats through integration of feature selection and stacking ensemble learning: the LGBM and random forest intrusion detection perspective
AK Mishra, S Paliwal - Cluster Computing, 2023 - Springer
The network traffic has observed astounding expansion and is set to explode in the next few
years. Security attacks are becoming more and more synchronized as attackers are involved …
years. Security attacks are becoming more and more synchronized as attackers are involved …
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 …
[HTML][HTML] Toward improved machine learning-based intrusion detection for Internet of Things traffic
S Alkadi, S Al-Ahmadi, MM Ben Ismail - Computers, 2023 - mdpi.com
The rapid development of Internet of Things (IoT) networks has revealed multiple security
issues. On the other hand, machine learning (ML) has proven its efficiency in building …
issues. On the other hand, machine learning (ML) has proven its efficiency in building …