Analysis of Current 5G Open-Source Projects

공개 소프트웨어 기반 5G 프로젝트 개발 동향 분석

  • Kim, M.J. ;
  • Park, K.M. ;
  • Park, J.G. ;
  • Kim, Y.S. ;
  • Lee, J.H. ;
  • Moon, D.S.
  • 김민재 (네트워크.시스템보안연구실) ;
  • 박경민 (네트워크.시스템보안연구실) ;
  • 박종근 (네트워크.시스템보안연구실) ;
  • 김영수 (네트워크.시스템보안연구실) ;
  • 이종훈 (네트워크.시스템보안연구실) ;
  • 문대성 (네트워크.시스템보안연구실)
  • Published : 2021.04.01


5G networks are rapidly expanding. Simultaneously, the need for a testbed-not a commercial network-is increasing to verify aspects such as 5G network security vulnerabilities. Open-source projects in 4G networks already exist and are implemented similarly in commercial networks. Due to the compatibilty between 5G and 4G networks, 5G networks are being developed and implemented as open-source projects on the basis of 4G networks. In this study, we review the development trends of 5G open-source projects and simulators that can be used for 5G research.



  1. 3gpp Release 15,
  2. OpenAirInterface,
  3. USRP X310,
  4. LimeSDR,
  5. 3gpp Release 16,
  6. srsLTE,
  7. ZeroMQ,
  8. S. R. Hussain et al., "LTEInspector: A systematic approach for adversarial testing of 4G LTE," in Proc. Network Distrib. Syst. Secur. (NDSS) Symp. San Diego, CA, USA, Feb. 2018.
  9. T. Fei and W. Wang, "LTE is vulnerable: Implementing identity spoofing and denial-of-service attacks in LTE networks," in Proc. IEEE Glob. Commun. Conf. (GLOBECOM) Waikoloa, HI, USA, Dec. 2019, pp. 1-6.
  10. M. Kim et al., "Long-term evolution vulnerability focusing on system information block messages," in Proc. Int. Conf. Inf. Commun. Technol. Convergence (ICTC) Jeju, Rep. of Korea, Oct. 2020, pp. 837-842.
  11. H. Kim et al., "Touching the untouchables: Dynamic security analysis of the LTE control plane," in Proc. IEEE Symp. Secur. Priv. (SP) San Francisco, CA, USA, May 2019.
  12. M. Echeverria et al., "PHOENIX: Device-centric cellular network protocol monitoring using runtime verification," arXiv preprint, CoRR, 2021, arXiv: 2101.00328v1.
  13. C. Lipps et al., "Keep private networks private: Secure channel-PUFs, and physical layer security by linear regression enhanced channel profiles," in Proc. 3rd Int. Conf. Data Intell. Secur. (ICDIS), South Padre Island, TX, USA, June 2020, pp. 93-100.
  14. Y.-J. Ku et al., "State of energy prediction in renewable energy-driven mobile edge computing using CNN-LSTM networks," in Proc. IEEE Green Energy Smart Syst. Conf. (IGESSC), Long Beach, CA, USA, Nov. 2020, pp. 1-7, 2020.
  15. T. Sandholm and S. Mukherjee, "A multi-armed bandit-based approach to mobile network provider selection," arXiv preprint, CoRR, 2020, arXiv: 2012.04755v2.
  16. OpenLTE,
  17. Open5GS,
  18. Open5GS,
  19. Free5GC,
  20. Free5GC,
  22. SD-RAN,
  23. N Patriciello et al., "An E2E simulator for 5G NR networks," Simul. Model. Pract. Theory, vol. 96, 2019, article number: 101933
  24. 5G-LENA,
  25. S. Martiradonna et al., "Understanding the 5G-air-simulator: A tutorial on design criteria, technical components, and reference use cases," Comput. Netw. vol. 177, 2020, article number: 107314.
  26. G. Piro et al., "Simulating LTE cellular systems: An open-source framework," IEEE Trans. Veh. Technol. vol. 60 no. 2, 2010, pp. 498-513.
  27. 5G-air-simulator,
  28. Netsim,
  29. nuXmv,
  30. S.R. Hussain et al., "5GReasoner: A property-directed security and privacy analysis framework for 5G cellular network protocol," in Proc. ACM SIGSAC Conf. Comput. Commun. Secur. London, UK, Nov. 2019, pp. 669-684.