Developing a Testbed with P4 to Generate Datasets for the Analysis of 5G-MEC Security

Service providers have now entered the implementation phase for 5G mobile telecommunication networks. With this, the concept of Multi-access Edge Computing (MEC) will play a crucial role when providing services on-the-go with low latency, high availability and high bandwidth. However, due to the low...

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Bibliographic Details
Main Authors: Fernando, Omesh A, Xiao, Hannan, Spring, Joseph
Format: Conference Proceeding
Language:English
Subjects:
5G mobile communication
5G-MEC
Bandwidth
Buildings
Communications technology
Conferences
Datasets
Employment
Multi-access edge computing
Network Attacks
Security
Testbed
UNSW NB-15
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Summary:Service providers have now entered the implementation phase for 5G mobile telecommunication networks. With this, the concept of Multi-access Edge Computing (MEC) will play a crucial role when providing services on-the-go with low latency, high availability and high bandwidth. However, due to the low processing power of MEC nodes, adversaries may target the platform for malevolent purposes. In this paper we focus on building a realistic 5G-MEC testbed to run legitimate traffic and network attacks, and to collect 5G datasets for 5G-MEC. We also apply a Convolutional Neural Network to the dataset created on our testbed and to publicly available datasets. Our datasets and detection rate suggest that the employment of current public datasets for research based on 5G-MEC security, is now inappropriate.
ISSN:1558-2612
DOI:10.1109/WCNC51071.2022.9771755