Synthetic Generation of Realistic Signal Strength Data to Enable 5G Rogue Base Station Investigation in Vehicular Platooning

Mohammad Saedi, Adrian Moore, Philip Perry, Christina Thorpe (Editor), Stephen O’ Shaughnessy (Editor)

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Rogue Base Stations (RBS), also known as 5G Subscription Concealed Identifier (SUCI) catchers, were initially developed to maliciously intercept subscribers’ identities. Since then, further advances have been made, not only in RBSs, but also in communication network security. The identification and prevention of RBSs in Fifth Generation (5G) networks are among the main security challenges for users and network infrastructure. The security architecture group in 3GPP clarified that the radio configuration information received from user equipment could contain fingerprints of the RBS. This information is periodically included in the measurement report generated by the user equipment to report location information and Received Signal Strength (RSS) measurements for the strongest base stations. The motivation in this work, then is to generate 5G measurement reports to provide a large and realistic dataset of radio information and RSS measurements for an autonomous vehicle driving along various sections of a road. These simulated measurement reports can then be used to develop and test new methods for identifying an RBS and taking mitigating actions. The proposed approach can generate 20 min of synthetic drive test data in 15 s, which is 80 times faster than real time.
Original languageEnglish
Article number12516
Pages (from-to)1-18
Number of pages18
JournalApplied Sciences
Issue number24
Publication statusPublished (in print/issue) - 7 Dec 2022

Bibliographical note

Funding Information:
This research has been supported by the BT Ireland Innovation Centre (BTIIC) project, funded by BT, and Invest Northern Ireland.

Publisher Copyright:
© 2022 by the authors.


  • Article
  • 5G mobile communication
  • autonomous vehicle
  • rogue base station
  • communication system security
  • measurement report
  • data generation


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