[HTML][HTML] Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future …
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
A survey on IoT intrusion detection: Federated learning, game theory, social psychology, and explainable AI as future directions
In the past several years, the world has witnessed an acute surge in the production and
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
Comparative analysis of intrusion detection systems and machine learning based model analysis through decision tree
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
[HTML][HTML] A federated learning framework for cyberattack detection in vehicular sensor networks
Abstract Vehicular Sensor Networks (VSN) introduced a new paradigm for modern
transportation systems by improving traffic management and comfort. However, the …
transportation systems by improving traffic management and comfort. However, the …
[HTML][HTML] Advanced feature-selection-based hybrid ensemble learning algorithms for network intrusion detection systems
As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems
(IDSs) are needed to monitor computer resources and to provide alerts regarding unusual or …
(IDSs) are needed to monitor computer resources and to provide alerts regarding unusual or …
[HTML][HTML] DIDS: A Deep Neural Network based real-time Intrusion detection system for IoT
M Vishwakarma, N Kesswani - Decision Analytics Journal, 2022 - Elsevier
The number of people using the Internet of Things (IoT) devices has exploded in recent
years. The instantaneous development in deploying constrained devices in numerous areas …
years. The instantaneous development in deploying constrained devices in numerous areas …
[HTML][HTML] XGB-RF: A hybrid machine learning approach for IoT intrusion detection
JA Faysal, ST Mostafa, JS Tamanna, KM Mumenin… - Telecom, 2022 - mdpi.com
In the past few years, Internet of Things (IoT) devices have evolved faster and the use of
these devices is exceedingly increasing to make our daily activities easier than ever …
these devices is exceedingly increasing to make our daily activities easier than ever …
[HTML][HTML] Ensemble-learning framework for intrusion detection to enhance internet of things' devices security
Y Alotaibi, M Ilyas - Sensors, 2023 - mdpi.com
The Internet of Things (IoT) comprises a network of interconnected nodes constantly
communicating, exchanging, and transferring data over various network protocols. Studies …
communicating, exchanging, and transferring data over various network protocols. Studies …
Feature engineering and machine learning framework for DDoS attack detection in the standardized internet of things
Over the past decade, there has been huge rise in the number of Internet of Things (IoT)
devices and networks often characterized by resource constraints on energy, memory …
devices and networks often characterized by resource constraints on energy, memory …
Towards SDN-enabled, intelligent intrusion detection system for internet of things (IoT)
The Internet of Things (IoT) has established itself as a multibillion-dollar business in recent
years. Despite its obvious advantages, the widespread nature of IoT renders it insecure and …
years. Despite its obvious advantages, the widespread nature of IoT renders it insecure and …