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A comprehensive review of the state-of-the-art on security and privacy issues in healthcare
Currently, healthcare is critical environment in our society, which attracts attention to
malicious activities and has caused an important number of damaging attacks. In parallel …
malicious activities and has caused an important number of damaging attacks. In parallel …
[HTML][HTML] Intrusion detection in internet of things systems: a review on design approaches leveraging multi-access edge computing, machine learning, and datasets
The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …
increase of network data and placed a high computation complexity across various …
Machine learning based IoT intrusion detection system: An MQTT case study (MQTT-IoT-IDS2020 dataset)
Abstract The Internet of Things (IoT) is one of the main research fields in the Cybersecurity
domain. This is due to (a) the increased dependency on automated device, and (b) the …
domain. This is due to (a) the increased dependency on automated device, and (b) the …
[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 …
A comprehensive survey for IoT security datasets taxonomy, classification and machine learning mechanisms
C Alex, G Creado, W Almobaideen, OA Alghanam… - Computers & …, 2023 - Elsevier
This survey paper compares existing IoT related datasets found in the literature with three
main objectives. The first one is to highlight the characteristics of these datasets such as the …
main objectives. The first one is to highlight the characteristics of these datasets such as the …
[HTML][HTML] Engineering the application of machine learning in an IDS based on IoT traffic flow
Abstract Internet of Things (IoT) devices are now widely used, enabling intelligent services
that, in association with new communication technologies like the 5G and broadband …
that, in association with new communication technologies like the 5G and broadband …
Machine learning-based adaptive synthetic sampling technique for intrusion detection
Traditional firewalls and data encryption techniques can no longer match the demands of
current IoT network security due to the rising amount and variety of network threats. In order …
current IoT network security due to the rising amount and variety of network threats. In order …
[PDF][PDF] A lightweight optimized deep learning-based host-intrusion detection system deployed on the edge for IoT
The Internet of Things (IoT) is now present in every domain from applications in smart
homes, Smart Cities, Industrial Internet of Things (IIoT), such as e-Health, and beyond. The …
homes, Smart Cities, Industrial Internet of Things (IIoT), such as e-Health, and beyond. The …
CPS attack detection under limited local information in cyber security: An ensemble multi-node multi-class classification approach
Cybersecurity breaches are common anomalies for distributed cyber-physical systems
(CPS). However, the cyber security breach classification is still a difficult problem, even …
(CPS). However, the cyber security breach classification is still a difficult problem, even …
Early network intrusion detection enabled by attention mechanisms and RNNs
Current flow-based Network Intrusion Detection Systems (NIDSs) have the drawback of
detecting attacks only once the flow has ended, resulting in potential delays in attack …
detecting attacks only once the flow has ended, resulting in potential delays in attack …