[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 …
A review and analysis of the bot-iot dataset
JM Peterson, JL Leevy… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Machine learning is rapidly changing the cybersecu-rity landscape. The use of predictive
models to detect malicious activity and identify inscrutable attack patterns is providing levels …
models to detect malicious activity and identify inscrutable attack patterns is providing levels …
Robust detection of unknown DoS/DDoS attacks in IoT networks using a hybrid learning model
The fourth industrial revolution is marked by the rapid growth of Internet of Things (IoT)
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …
DeBot: A deep learning-based model for bot detection in industrial internet-of-things
In this paper, we show a deep learning model for bot detection, named as DeBot, for
industrial network traffic. DeBot uses a novel Cascade Forward Back Propagation Neural …
industrial network traffic. DeBot uses a novel Cascade Forward Back Propagation Neural …
[HTML][HTML] Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring
Abstract The application of Deep Neural Networks (DNNs) for monitoring cyberattacks in
Internet of Things (IoT) systems has gained significant attention in recent years. However …
Internet of Things (IoT) systems has gained significant attention in recent years. However …
An intrusion detection system using BoT-IoT
S Alosaimi, SM Almutairi - Applied Sciences, 2023 - mdpi.com
The rapid growth of the Internet of Things (IoT) has led to an increased automation and
interconnectivity of devices without requiring user intervention, thereby enhancing the …
interconnectivity of devices without requiring user intervention, thereby enhancing the …
A hybrid deep learning approach for bottleneck detection in IoT
Cloud computing is perhaps the most enticing innovation in the present figuring situation. It
gives an expense-effective arrangement by diminishing the enormous forthright expense of …
gives an expense-effective arrangement by diminishing the enormous forthright expense of …
IoT Security Based on Machine Learning
RK Vanakamamidi, L Ramalingam… - … For Smart Nation …, 2023 - ieeexplore.ieee.org
The protection of user privacy and mitigation of threats like spoofing, DoS, jamming, and
eavesdropping are essential for the Internets of Things (IoT) to fulfill its promise of bringing …
eavesdropping are essential for the Internets of Things (IoT) to fulfill its promise of bringing …
Approach for detecting attacks on IoT networks based on ensemble feature selection and deep learning models
The Internet of Things (IoT) has transformed our interaction with technology and introduced
security challenges. The growing number of IoT attacks poses a significant threat to …
security challenges. The growing number of IoT attacks poses a significant threat to …
An anomaly intrusion detection for high-density internet of things wireless communication network based deep learning algorithms
Telecommunication networks are growing exponentially due to their significant role in
civilization and industry. As a result of this very significant role, diverse applications have …
civilization and industry. As a result of this very significant role, diverse applications have …