Fake Base Station 5G

Citation Author(s):
Roger William
Coêlho
State University of Maringá (UEM)
Ronan
Assumpção Silva
Federal Institute of Paraná (IFPR)
Luciana Andréia
Fondazzi Martimiano
State University of Maringá (UEM)
Elvio João
Leonardo
State University of Maringá (UEM)
Submitted by:
Roger Coelho
Last updated:
Thu, 12/12/2024 - 15:21
DOI:
10.21227/rgb4-fk52
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Abstract 

The 5G cellular technology has introduced advanced radio communication protocols and new frequency bands and enabled faster data exchange. These improvements increase network capacity and establish a foundation for high-bandwidth, low-latency services, helping the development of applications like the Internet of Things (IoT). However, information security poses significant challenges, particularly concerning attacks such as Fake Base Stations (FBS) and Stream Control Transmission Protocol (SCTP) Session Hijacking. This study employs Supervised Machine Learning techniques to classify FBS attack involving SCTP Session Hijacking and to identify the most effective learning models.

Instructions: 

Use machine learning algorithms.

Funding Agency: 
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Grant Number: 
88887.941768/2024-00