Detail publikačního výsledku

Deep Learning-Based Radio Frequency Identification of False Base Stations

BOLCEK, J.; KUFA, J.; HARVÁNEK, M.; POLÁK, L.; KRÁL, J.; MARŠÁLEK, R.

Originální název

Deep Learning-Based Radio Frequency Identification of False Base Stations

Anglický název

Deep Learning-Based Radio Frequency Identification of False Base Stations

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

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

Klíčová slova v angličtině

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

Autoři

BOLCEK, J.; KUFA, J.; HARVÁNEK, M.; POLÁK, L.; KRÁL, J.; MARŠÁLEK, R.

Rok RIV

2024

Vydáno

21.11.2023

Nakladatel

IEEE

Místo

Riga, Latvia

ISBN

979-8-3503-9349-1

Kniha

2023 Workshop on Microwave Theory and Technology in Wireless Communications (MTTW)

Strany od

45

Strany do

49

Strany počet

5

URL

https://ieeexplore.ieee.org/document/10320078

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"
}