Results 51 to 60 of about 4,251 (194)
Internet of Things technology opens the horizon to a broader scope of intelligent applications in smart cities. However, the massive amount of traffic exchanged among devices may cause security risks, especially when devices are compromised or vulnerable
Moody Alhanaya, Khalil Al-Shqeerat
doaj +1 more source
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha +9 more
wiley +1 more source
Graph neural network‐based attack prediction for communication‐based train control systems
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
Malicious Network Traffic Detection Based on Deep Neural Networks and Association Analysis
Anomaly detection systems can accurately identify malicious network traffic, providing network security. With the development of internet technology, network attacks are becoming more and more sourced and complicated, making it difficult for traditional ...
Minghui Gao +5 more
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Malicious Traffic Classification via Edge Intelligence in IIoT
The proliferation of smart devices in the 5G era of industrial IoT (IIoT) produces significant traffic data, some of which is encrypted malicious traffic, creating a significant problem for malicious traffic detection. Malicious traffic classification is
Maoli Wang +4 more
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Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Abstract The Internet of Things (IoT) in deploying robotic sprayers for pandemic‐associated disinfection and monitoring has garnered significant attention in recent research. The authors introduce a novel architectural framework designed to interconnect smart monitoring robotic devices within healthcare facilities using narrowband Internet of Things ...
Md Motaharul Islam +9 more
wiley +1 more source
ABSTRACT Networked control systems (NCSs) often suffer from performance degradation due to limited communication bandwidth, which can cause data transmission conflicts and packet loss. Existing scheduling strategies may fail to simultaneously meet the real‐time requirements and the importance of multisensor data, and they are particularly vulnerable ...
Da Chen +5 more
wiley +1 more source
A Credibility Score Algorithm for Malicious Data Detection in Urban Vehicular Networks
This paper introduces a method to detect malicious data in urban vehicular networks, where vehicles report their locations to road-side units controlling traffic signals at intersections.
Bartłomiej Płaczek +2 more
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ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim +4 more
wiley +1 more source

