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A comprehensive survey of generative adversarial networks (GANs) in cybersecurity intrusion detection
Generative Adversarial Networks (GANs) have seen significant interest since their
introduction in 2014. While originally focused primarily on image-based tasks, their capacity …
introduction in 2014. While originally focused primarily on image-based tasks, their capacity …
In-depth feature selection for the statistical machine learning-based botnet detection in IoT networks
Attackers compromise insecure IoT devices to expand their botnets in order to launch more
influential attacks against their victims. In various studies, machine learning has been used …
influential attacks against their victims. In various studies, machine learning has been used …
Real-time botnet detection on large network bandwidths using machine learning
Botnets are one of the most harmful cyberthreats, that can perform many types of
cyberattacks and cause billionaire losses to the global economy. Nowadays, vast amounts …
cyberattacks and cause billionaire losses to the global economy. Nowadays, vast amounts …
Unsupervised learning for feature selection: A proposed solution for botnet detection in 5g networks
The world has seen exponential growth in deploying Internet of Things (IoT) devices. In
recent years, connected IoT devices have surpassed the number of connected non-IoT …
recent years, connected IoT devices have surpassed the number of connected non-IoT …
Urban Mobility Pattern Detection: Development of a Classification Algorithm Based on Machine Learning and GPS
This study introduces an innovative algorithm for classifying transportation modes. It
categorizes modes such as walking, biking, tram, bus, taxi, and private vehicles based on …
categorizes modes such as walking, biking, tram, bus, taxi, and private vehicles based on …
Machine learning for botnet detection: An optimized feature selection approach
Technological advancements have been evolving for so long, particularly Internet of Things
(IoT) technology that has seen an increase in the number of connected devices surpass non …
(IoT) technology that has seen an increase in the number of connected devices surpass non …
PhiKitA: Phishing kit attacks dataset for phishing websites identification
Recent studies have shown that phishers are using phishing kits to deploy phishing attacks
faster, easier and more massive. Detecting phishing kits in deployed websites might help to …
faster, easier and more massive. Detecting phishing kits in deployed websites might help to …
[HTML][HTML] Internet of Things botnets: A survey on Artificial Intelligence based detection techniques
Abstract The Internet of Things (IoT) is a game changer when it comes to digitization across
industries. The Fourth Industrial Revolution (4IR), brought about a paradigm shift indeed …
industries. The Fourth Industrial Revolution (4IR), brought about a paradigm shift indeed …
An evolutionary computation-based machine learning for network attack detection in big data traffic
Y Wang, H Zhang, Y Wei, H Wang, Y Peng, Z Bin… - Applied Soft …, 2023 - Elsevier
Big data scenarios are characterized by multiple devices, massive traffic, and high data
dimensionality. In the process of attack identification, the selection of features from massive …
dimensionality. In the process of attack identification, the selection of features from massive …
EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids
Reliability and security of power distribution and data traffic in smart grid (SG) are very
important for industrial control systems (ICS). Indeed, SG cyber-physical connectivity is …
important for industrial control systems (ICS). Indeed, SG cyber-physical connectivity is …