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Ensemble-learning framework for intrusion detection to enhance internet of things' devices security
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 …
[HTML][HTML] TNN-IDS: Transformer neural network-based intrusion detection system for MQTT-enabled IoT Networks
Abstract The Internet of Things (IoT) is a global network that connects a large number of
smart devices. MQTT is a de facto standard, lightweight, and reliable protocol for machine-to …
smart devices. MQTT is a de facto standard, lightweight, and reliable protocol for machine-to …
[PDF][PDF] A hybrid deep learning-based intrusion detection system for IoT networks
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 lightweight double-stage scheme to identify malicious DNS over HTTPS traffic using a hybrid learning approach
The Domain Name System (DNS) protocol essentially translates domain names to IP
addresses, enabling browsers to load and utilize Internet resources. Despite its major role …
addresses, enabling browsers to load and utilize Internet resources. Despite its major role …
[PDF][PDF] Multi-step attack detection in industrial networks using a hybrid deep learning architecture
In recent years, the industrial network has seen a number of high-impact attacks. To counter
these threats, several security systems have been implemented to detect attacks on …
these threats, several security systems have been implemented to detect attacks on …
[HTML][HTML] Evaluating ensemble learning mechanisms for predicting advanced cyber attacks
F Alserhani, A Aljared - Applied Sciences, 2023 - mdpi.com
With the increased sophistication of cyber-attacks, there is a greater demand for effective
network intrusion detection systems (NIDS) to protect against various threats. Traditional …
network intrusion detection systems (NIDS) to protect against various threats. Traditional …
[PDF][PDF] Enhancing IoT network defense: advanced intrusion detection via ensemble learning techniques
The Internet of Things (IoT) has evolved significantly, automating daily activities by
connecting numerous devices. However, this growth has increased cybersecurity threats …
connecting numerous devices. However, this growth has increased cybersecurity threats …
Recurrent Neural Network based Incremental model for Intrusion Detection System in IoT
The security of Internet of Things (IoT) networks has become a integral problem in view of
the exponential growth of IoT devices. Intrusion detection and prevention is an approach …
the exponential growth of IoT devices. Intrusion detection and prevention is an approach …
Real-time human activity recognition from smart phone using linear support vector machines
K Maaloul, L Brahim… - … Electronics and Control), 2023 - telkomnika.uad.ac.id
The recognition of human activity (HAR) the use of cell devices embedded in its exten sively
disbursed sensors affords guidance, instructions, and take care of citizens of smart cities …
disbursed sensors affords guidance, instructions, and take care of citizens of smart cities …
Enhance the Detection of DoS and Brute Force Attacks within the MQTT Environment through Feature Engineering and Employing an Ensemble Technique
AA Hanif, M Ilyas - arxiv preprint arxiv:2408.00480, 2024 - arxiv.org
The rapid development of the Internet of Things (IoT) environment has introduced
unprecedented levels of connectivity and automation. The Message Queuing Telemetry …
unprecedented levels of connectivity and automation. The Message Queuing Telemetry …