An Autoencoder-based Multi-task Learning for Intrusion Detection in IoT Networks
The size of Internet of Things (IoT) networks, the physical devices connected to them, and
the volume of data processed have grown exponentially over the past decade. Meanwhile …
the volume of data processed have grown exponentially over the past decade. Meanwhile …
A multi-layer classification approach for intrusion detection in iot networks based on deep learning
The security of IoT networks is an important concern to researchers and business owners,
which is taken into careful consideration due to its direct impact on the availability of the …
which is taken into careful consideration due to its direct impact on the availability of the …
A comparative analysis of machine learning algorithms for intrusion detection in edge-enabled IoT networks
P Mahadevappa, SM Muzammal… - arXiv preprint arXiv …, 2021 - arxiv.org
A significant increase in the number of interconnected devices and data communication
through wireless networks has given rise to various threats, risks and security concerns …
through wireless networks has given rise to various threats, risks and security concerns …
A Stacking Ensemble of Deep Learning Models for IoT Network Intrusion Detection
R Lazzarini, H Tianfield, P Charissis - A Stacking Ensemble of …, 2023 - papers.ssrn.com
The number of Internet of Things (IoT) devices has increased considerably in the past few
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …
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 …
Hybrid Multi-Task Deep Learning for Improved IoT Network Intrusion Detection: Exploring Different CNN Structures
The rapid expansion of the Internet of Things (IoT) has led to the need for robust security
mechanisms to protect IoT networks and devices against various attacks. In this paper, we …
mechanisms to protect IoT networks and devices against various attacks. In this paper, we …
Efficient Network Traffic Feature Sets for IoT Intrusion Detection
The use of Machine Learning (ML) models in cybersecurity solutions requires high-quality
data that is stripped of redundant, missing, and noisy information. By selecting the most …
data that is stripped of redundant, missing, and noisy information. By selecting the most …
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 …
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 …
Deep learning-based intrusion detection for IoT networks
Internet of Things (IoT) has an immense potential for a plethora of applications ranging from
healthcare automation to defence networks and the power grid. The security of an IoT …
healthcare automation to defence networks and the power grid. The security of an IoT …