Deep learning approach for SDN-enabled intrusion detection system in IoT networks
Owing to the prevalence of the Internet of things (IoT) devices connected to the Internet, the
number of IoT-based attacks has been growing yearly. The existing solutions may not …
number of IoT-based attacks has been growing yearly. The existing solutions may not …
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 …
Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach
Abstract The Internet of Things (IoT) is currently seeing tremendous growth due to new
technologies and big data. Research in the field of IoT security is an emerging topic. IoT …
technologies and big data. Research in the field of IoT security is an emerging topic. IoT …
RETRACTED ARTICLE: FSO-LSTM IDS: hybrid optimized and ensembled deep-learning network-based intrusion detection system for smart networks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 …
WILS-TRS—A novel optimized deep learning based intrusion detection framework for IoT networks
B Jothi, M Pushpalatha - Personal and Ubiquitous Computing, 2023 - Springer
Abstract Internet of Things (IoT) and its applications have gained importance in recent times
of research. The heterogeneous nature of IoT networks makes them applicable for various …
of research. The heterogeneous nature of IoT networks makes them applicable for various …
Machine learning-driven intrusion detection for Contiki-NG-based IoT networks exposed to NSL-KDD dataset
Wide adoption of Internet of Things (IoT) devices and applications encounters security
vulnerabilities as roadblocks. The heterogeneous nature of IoT systems prevents common …
vulnerabilities as roadblocks. The heterogeneous nature of IoT systems prevents common …
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 …
A lightweight supervised intrusion detection mechanism for IoT networks
S Roy, J Li, BJ Choi, Y Bai - Future Generation Computer Systems, 2022 - Elsevier
Abstract As the Internet of Things (IoT) is becoming increasingly popular, we have
experienced more security breaches that are associated with the connection of vulnerable …
experienced more security breaches that are associated with the connection of vulnerable …
[HTML][HTML] Enhancing IoT network security through deep learning-powered Intrusion Detection System
The rapid growth of the Internet of Things (IoT) has brought about a global concern for the
security of interconnected devices and networks. This necessitates the use of efficient …
security of interconnected devices and networks. This necessitates the use of efficient …
Transfer-learning-based intrusion detection framework in IoT networks
Cyberattacks in the Internet of Things (IoT) are growing exponentially, especially zero-day
attacks mostly driven by security weaknesses on IoT networks. Traditional intrusion …
attacks mostly driven by security weaknesses on IoT networks. Traditional intrusion …