Ai-based two-stage intrusion detection for software defined iot networks
Software defined Internet of Things (SD-IoT) networks profit from centralized management
and interactive resource sharing, which enhances the efficiency and scalability of Internet of …
and interactive resource sharing, which enhances the efficiency and scalability of Internet of …
Anomaly detection on iot network intrusion using machine learning
Enhancing the security of IoT networks is trending as one of the most crucial issues the
information technology community faces. With large scales of IoT devices being developed …
information technology community faces. With large scales of IoT devices being developed …
Deep learning feature fusion approach for an intrusion detection system in SDN-based IoT networks
V Ravi, R Chaganti, M Alazab - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
A survey of the literature shows that the number of IoT attacks are gradually growing over the
years due to the growing trend of Internet-enabled devices. Software defined networking …
years due to the growing trend of Internet-enabled devices. Software defined networking …
[HTML][HTML] Deep learning for cyber threat detection in IoT networks: A review
A Aldhaheri, F Alwahedi, MA Ferrag, A Battah - Internet of Things and Cyber …, 2023 - Elsevier
Abstract The Internet of Things (IoT) has revolutionized modern tech with interconnected
smart devices. While these innovations offer unprecedented opportunities, they also …
smart devices. While these innovations offer unprecedented opportunities, they also …
RETRACTED ARTICLE: FSO-LSTM IDS: hybrid optimized and ensembled deep-learning network-based intrusion detection system for smart networks
AS Alqahtani - The Journal of Supercomputing, 2022 - Springer
Abstract The Internet of Things (IoT) has achieved exponential growth worldwide. Although
the IoT is used by millions of users, these networks are handicapped by attacks such as …
the IoT is used by millions of users, these networks are handicapped by attacks such as …
Feature analysis for machine learning-based IoT intrusion detection
Internet of Things (IoT) networks have become an increasingly attractive target of
cyberattacks. Powerful Machine Learning (ML) models have recently been adopted to …
cyberattacks. Powerful Machine Learning (ML) models have recently been adopted to …
An efficient deep-learning-based detection and classification system for cyber-attacks in IoT communication networks
Q Abu Al-Haija, S Zein-Sabatto - Electronics, 2020 - mdpi.com
With the rapid expansion of intelligent resource-constrained devices and high-speed
communication technologies, the Internet of Things (IoT) has earned wide recognition as the …
communication technologies, the Internet of Things (IoT) has earned wide recognition as the …
Semisupervised-learning-based security to detect and mitigate intrusions in IoT network
N Ravi, SM Shalinie - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
Our world is moving toward an Internet of Things (IoT) era by connecting billions of IoT.
There are several security loopholes in the IoT network. Intrusion can lead to performance …
There are several security loopholes in the IoT network. Intrusion can lead to performance …
Dependable intrusion detection system for IoT: A deep transfer learning based approach
Security concerns for Internet of Things (IoT) applications have been alarming because of
their widespread use in different enterprise systems. The potential threats to these …
their widespread use in different enterprise systems. The potential threats to these …
A comprehensive deep learning benchmark for IoT IDS
The significance of an intrusion detection system (IDS) in networks security cannot be
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …
overstated in detecting and responding to malicious attacks. Failure to detect large-scale …