IoT intrusion detection using machine learning with a novel high performing feature selection method
The Internet of Things (IoT) ecosystem has experienced significant growth in data traffic and
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self …
Classification and explanation for intrusion detection system based on ensemble trees and SHAP method
In recent years, many methods for intrusion detection systems (IDS) have been designed
and developed in the research community, which have achieved a perfect detection rate …
and developed in the research community, which have achieved a perfect detection rate …
MidSiot: A multistage intrusion detection system for internet of things
N Dat-Thinh, H Xuan-Ninh… - … and Mobile Computing, 2022 - Wiley Online Library
Internet of Things (IoT) has been thriving in recent years, playing an important role in a
multitude of various domains, including industry 4.0, smart transportation, home automation …
multitude of various domains, including industry 4.0, smart transportation, home automation …
[PDF][PDF] A hybrid deep learning-based intrusion detection system for IoT networks
NW Khan, MS Alshehri, MA Khan, S Almakdi… - Math. Biosci …, 2023 - aimspress.com
The Internet of Things (IoT) is a rapidly evolving technology with a wide range of potential
applications, but the security of IoT networks remains a major concern. The existing system …
applications, but the security of IoT networks remains a major concern. The existing system …
A Survey of Deep Learning Technologies for Intrusion Detection in Internet of Things
The Internet of Things (IoT) is transforming how we live and work, and its applications are
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
Toward Enhanced Attack Detection and Explanation in Intrusion Detection System-Based IoT Environment Data
RW Wardhani, DSC Putranto, U Jo, H Kim - IEEE Access, 2023 - ieeexplore.ieee.org
Securing the Internet of Things (IoT) against cyber threats is a formidable challenge, and
Intrusion Detection Systems (IDS) play a critical role in this effort. However, the lack of …
Intrusion Detection Systems (IDS) play a critical role in this effort. However, the lack of …
Inverse design of aluminium alloys using genetic algorithm: a class-based workflow
The design of aluminium alloys often encounters a trade-off between strength and ductility,
making it challenging to achieve desired properties. Adding to this challenge is the broad …
making it challenging to achieve desired properties. Adding to this challenge is the broad …
An intelligent machine learning based intrusion detection system (IDS) for smart cities networks
Abstract INTRODUCTION: Internet of Things (IoT) along with Cloud based systems are
opening a new domain of development. They have several applications from smart homes …
opening a new domain of development. They have several applications from smart homes …
GAMA: A multi-graph-based anomaly detection framework for business processes via graph neural networks
Anomalies in business processes are inevitable for various reasons such as system failures
and operator errors. Detecting anomalies is important for the management and optimization …
and operator errors. Detecting anomalies is important for the management and optimization …
PnT: Born-again tree-based model via fused decision path encoding
N Cohen-Shapira, L Rokach - Information Fusion, 2024 - Elsevier
Decision forests, such as random forest (RF) are widely used for tabular data, mainly due to
their predictive performance and ease of usage. However, given that the forest's trees may …
their predictive performance and ease of usage. However, given that the forest's trees may …