Machine Learning Techniques for Detecting Attackers During Quantum Key Distribution in IoT Networks With Application to Railway Scenarios

Machine Learning Techniques for Detecting Attackers During Quantum Key Distribution in IoT Networks With Application to Railway Scenarios

<p>Internet of Things (IoT) deployments face significant security challenges due to the limited energy and computational power of IoT devices. These challenges are more serious in the quantum communications era, where certain attackers might have quantum computing capabilities, which renders I...

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Bibliographic Details
Main Author: Hasan Abbas Al-Mohammed (16810674) (author)
Other Authors: Afnan Al-Ali (16888695) (author), Elias Yaacoub (14150586) (author), Uvais Qidwai (16888698) (author), Khalid Abualsaud (16888701) (author), Stanislaw Rzewuski (16888704) (author), Adam Flizikowski (16888707) (author)
Published: 2021
Subjects:
Engineering
Communications engineering
Information and computing sciences
Distributed computing and systems software
Machine learning
Photonics
Servers
Artificial neural networks
5G mobile communication
Receivers
Radio frequency
5G and beyond
IoT security
Quantum key distribution
Railway communications
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