Network intrusion detection for IoT security based on learning techniques
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
DEMISe: Interpretable deep extraction and mutual information selection techniques for IoT intrusion detection
LR Parker, PD Yoo, TA Asyhari, L Chermak… - Proceedings of the 14th …, 2019 - dl.acm.org
Recent studies have proposed that traditional security technology--involving pattern-
matching algorithms that check predefined pattern sets of intrusion signatures--should be …
matching algorithms that check predefined pattern sets of intrusion signatures--should be …
FeCo: Boosting intrusion detection capability in IoT networks via contrastive learning
Over the last decade, Internet of Things (IoT) has permeated our daily life with a broad range
of applications. However, a lack of sufficient security features in IoT devices renders IoT …
of applications. However, a lack of sufficient security features in IoT devices renders IoT …
[HTML][HTML] A lightweight SEL for attack detection in IoT/IIoT networks
SA Abdulkareem, CH Foh, F Carrez… - Journal of Network and …, 2024 - Elsevier
Intrusion detection systems (IDSs) that continuously monitor data flow and take swift action
when attacks are identified safeguard networks. Conventional IDS exhibit limitations, such …
when attacks are identified safeguard networks. Conventional IDS exhibit limitations, such …
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 …
A deep learning methodology for predicting cybersecurity attacks on the internet of things
OA Alkhudaydi, M Krichen, AD Alghamdi - Information, 2023 - mdpi.com
With the increasing severity and frequency of cyberattacks, the rapid expansion of smart
objects intensifies cybersecurity threats. The vast communication traffic data between …
objects intensifies cybersecurity threats. The vast communication traffic data between …
Machine learning-based intrusion detection: feature selection versus feature extraction
Abstract Internet of Things (IoTs) has been playing an important role in many sectors, such
as smart cities, smart agriculture, smart healthcare, and smart manufacturing. However, IoT …
as smart cities, smart agriculture, smart healthcare, and smart manufacturing. However, IoT …
[HTML][HTML] A stacking ensemble of deep learning models for IoT intrusion detection
R Lazzarini, H Tianfield, V Charissis - Knowledge-Based Systems, 2023 - Elsevier
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 …
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 …
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 …