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Project detail
Duration: 01.01.2023 — 31.12.2025
Funding resources
Ministerstvo vnitra ČR - 1 VS OPSEC
- whole funder
On the project
Description in EnglishAccesible software and hardware resources will allow for the rapid development and diversification of 5G networks. On the other hand, they can pose significant security risks. One of the risks identified in the Report on the cybersecurity of Open RAN, released by the NIS Cooperation Group in May 2022, is the use of 5G networks within organized crime. One of the technical means of such misuse can be, for example, identity of 5G base stations, where an attacker gains complete access to the operation of part of the network and user data. The aim of the project is to propose appropriate measures and verify the real possibility of their use to provide additional security against stoling the identity of 5G base stations, both closed networks, but especially of Open RAN networks.
Key words in Englishmobile network cybersecurity, identity falsification
Mark
VK01030166
Default language
Czech
People responsible
Blumenstein Jiří, doc. Ing., Ph.D. - fellow researcherBolcek Jan, Ing. - fellow researcherHanus Stanislav, prof. Ing., CSc. - fellow researcherHarvánek Michal, Ing., Ph.D. - fellow researcherKufa Jan, Ing., Ph.D. - fellow researcherMaršálek Roman, prof. Ing., Ph.D. - fellow researcherŠimka Marek, Ing. - fellow researcherUrbanec Tomáš, Ing., Ph.D. - fellow researcherVychodil Josef, Ing., Ph.D. - fellow researcherPolák Ladislav, doc. Ing., Ph.D. - principal person responsible
Units
Department of Radio Electronics- (2022-05-26 - not assigned)
Results
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.Detail