Result Details

Deep Learning-Based Radio Frequency Identification of False Base Stations

BOLCEK, J.; KUFA, J.; HARVÁNEK, M.; POLÁK, L.; KRÁL, J.; MARŠÁLEK, R. Deep Learning-Based Radio Frequency Identification of False Base Stations. In 2023 Workshop on Microwave Theory and Technology in Wireless Communications (MTTW). Riga, Latvia: IEEE, 2023. p. 45-49. ISBN: 979-8-3503-9349-1.
Type
conference paper
Language
English
Authors
Bolcek Jan, Ing., UREL (FEEC)
Kufa Jan, Ing., Ph.D., UREL (FEEC)
Harvánek Michal, Ing., Ph.D., UREL (FEEC)
Polák Ladislav, doc. Ing., Ph.D., UREL (FEEC)
Král Jan, Ing., Ph.D., UREL (FEEC)
Maršálek Roman, prof. Ing., Ph.D., UREL (FEEC)
Abstract

Advances in mobile and wireless communications allow to handle the continuously increasing demands on the data volume and connectivity of users. The 5G Open Radio Access Network (RAN) concept offers a flexible and inter-operable solution enabling network operators to select equipment from different vendors. However, such a step can potentially increase security risks due to emergence of the false base stations (FBS) operated with a purpose to steal private information about mobile equipment users. In this paper, we introduce a simple deep-learning (DL) based classification method, working directly with In-phase and Quadrature (I/Q) data of a radio frequency (RF) signal, to identify a device working as FBS. To operate the legitimate as well as the FBS, the srsRAN open-source software suite from Software Radio Systems (SRS), connected to three distinct software defined radio (SDR) devices, is used.

Keywords

5G Open RAN, 4G/5G SRS RAN, Deep Learning, RF measurement, I/Q-data

URL
Published
2023
Pages
45–49
Proceedings
2023 Workshop on Microwave Theory and Technology in Wireless Communications (MTTW)
Conference
IEEE Microwave Theory and Techniques in Wireless Communications (MTTW)
ISBN
979-8-3503-9349-1
Publisher
IEEE
Place
Riga, Latvia
DOI
10.1109/MTTW59774.2023.10320078
EID Scopus
2-s2.0-85179550671
BibTeX 
@inproceedings{BUT185786,
  author="Jan {Bolcek} and Jan {Kufa} and Michal {Harvánek} and Ladislav {Polák} and Jan {Král} and Roman {Maršálek}",
  title="Deep Learning-Based Radio Frequency Identification of False Base Stations",
  booktitle="2023 Workshop on Microwave Theory and Technology in Wireless Communications (MTTW)",
  year="2023",
  pages="45--49",
  publisher="IEEE",
  address="Riga, Latvia",
  doi="10.1109/MTTW59774.2023.10320078",
  isbn="979-8-3503-9349-1",
  url="https://ieeexplore.ieee.org/document/10320078"
}
Departments
Ústav radioelektroniky (UREL)
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