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BOLCEK, J. KUFA, J. HARVÁNEK, M. POLÁK, L. KRÁL, J. MARŠÁLEK, R.
Original Title
Deep Learning-Based Radio Frequency Identification of False Base Stations
Type
conference paper
Language
English
Original 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
Authors
BOLCEK, J.; KUFA, J.; HARVÁNEK, M.; POLÁK, L.; KRÁL, J.; MARŠÁLEK, R.
Released
21. 11. 2023
Publisher
IEEE
Location
Riga, Latvia
ISBN
979-8-3503-9349-1
Book
2023 Workshop on Microwave Theory and Technology in Wireless Communications (MTTW)
Pages from
45
Pages to
49
Pages count
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" }