Abstract
The vulnerability of 5G networks to jamming attacks has emerged as a significant concern. This paper contributes in two primary aspects. Firstly, it investigates the effect of a multi-jammer on 5G cell metrics, specifically throughput and goodput. The investigation is conducted within the context of a mobility model for user equipment (UE), with a focus on scenarios involving connected vehicles (CVs) engaged in a mission. Secondly, the vulnerability of synchronization signal block (SSB) components is examined concerning jamming power and beam sweeping. Notably, the study reveals that increasing jamming power beyond 40 dBm blackin our specific scenario configuration no longer decreases network throughput due to the re-transmission of packets through the hybrid automatic repeat request (HARQ) process. Furthermore, it is observed that under the same jamming power, the physical downlink shared channel (PDSCH) is more vulnerable than the primary synchronization signal (PSS) and secondary synchronization signal (SSS). However, a smart jammer can disrupt the cell search process by injecting less power and targeting PSS-SSS or physical broadcast channel (PBCH) data compared to a barrage jammer. On the other hand, beam sweeping proves effective in mitigating the impact of a smart jammer, reducing the error vector magnitude root mean square from 51.59% to 23.36% under the same jamming power.
References
J. Cao, M. Ma, H. Li, R. Ma, Y. Sun, P. Yu, and L. Xiong, “A survey on security aspects for 3gpp 5g networks,” IEEE Commun. Surveys & Tutorials, vol. 22, no. 1, pp. 170–195, 2020.
S. Sullivan, A. Brighente, S. A. P. Kumar, and M. Conti, “5g security challenges and solutions: A review by OSI layers,” IEEE Access, vol. 9, pp. 116 294–116 314, 2021.
A. Chorti, A. N. Barreto, S. Köpsell, M. Zoli, M. Chafii, P. Sehier, G. Fettweis, and H. V. Poor, “Context-aware security for 6g wireless: The role of physical layer security,” IEEE Commun. Standards Magazine, vol. 6, no. 1, pp. 102–108, 2022.
H. Pirayesh and H. Zeng, “Jamming attacks and anti-jamming strategies in wireless networks: A comprehensive survey,” IEEE Communications Surveys & Tutorials, vol. 24, no. 2, pp. 767–809, 2022.
A. Mpitziopoulos, D. Gavalas, C. Konstantopoulos, and G. Pantziou, “A survey on jamming attacks and countermeasures in WSNs,” IEEE Commun. Surveys & Tutorials, vol. 11, no. 4, pp. 42–56, 2009.
M. A. Birutis and A. Mykkeltveit, “Practical jamming of a commercial 5g radio system at 3.6 ghz,” Procedia Computer Science, vol. 205, pp. 58–67, 2022.
A. D. Nguyen, P. Sénac, V. Ramiro, and M. Diaz, “Steps - an approach for human mobility modeling,” in 10th IFIP Networking Conference. Valencia, Spain: Springer Berlin Heidelberg, May 2011, pp. 254–265.
Y. Arjoune and S. Faruque, “Smart jamming attacks in 5g new radio: A review,” in 10th Annual Computing and Communication Workshop and Conf. (CCWC). IEEE, 2020, pp. 1010–1015.
M. Lichtman, R. Rao, V. Marojevic, J. Reed, and R. P. Jover, “5g nr jamming, spoofing, and sniffing: Threat assessment and mitigation,” in IEEE Int. Conf. on Communications Workshops (ICC Workshops). IEEE, 2018, pp. 1–6.
M. E. Flores, D. D. Poisson, C. J. Stevens, A. V. Nieves, and A. M. Wyglinski, “Implementation and evaluation of a smart uplink jamming attack in a public 5g network,” IEEE Access, 2023.
K. Grover, A. Lim, and Q. Yang, “Jamming and anti–jamming techniques in wireless networks: a survey,” Intl. Journal of Ad Hoc and Ubiquitous Computing, vol. 17, no. 4, pp. 197–215, 2014.
Y. O. Basciftci, F. Chen, J. Weston, R. Burton, and C. E. Koksal, “How vulnerable is vehicular communication to physical layer jamming attacks?” in 2015 IEEE 82nd Veh. Tech. Conf. (VTC2015-Fall), 2015, pp. 1–5.
P. Angueira, I. Val, J. Montalbán, O. Seijo, E. Iradier, P. S. Fontaneda, L. Fanari, and A. Arriola, “A survey of physical layer techniques for secure wireless communications in industry,” IEEE Commun. Surveys & Tutorials, vol. 24, no. 2, pp. 810–838, 2022.
C. D. T. Thai, V.-N. Q. Bao, and N.-S. Vo, “Secure communication using interference cancellation against multiple jammers,” IEEE Trans. on Veh. Techn., vol. 71, no. 12, pp. 12 811–12 825, 2022.
P. Tague, D. Slater, R. Poovendran, and G. Noubir, “Linear programming models for jamming attacks on network traffic flows,” in 6th Intl. Symp. on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks and Workshops. IEEE, 2008, pp. 207–216.
T. Cheng, P. Li, S. Zhu, and D. Torrieri, “M-cluster and x-ray: Two methods for multi-jammer localization in wireless sensor networks,” Integrated Computer-Aided Engineering, vol. 21, no. 1, pp. 19–34, 2014.
Z. Liu, H. Liu, W. Xu, and Y. Chen, “An error-minimizing framework for localizing jammers in wireless networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 2, pp. 508–517, 2013.
A. O. F. Atya, A. Aqil, S. Singh, I. Broustis, K. Sundaresan, and S. V. Krishnamurthy, “Exploiting subcarrier agility to alleviate active jamming attacks in wireless networks,” IEEE Transactions on Mobile Computing, vol. 14, no. 12, pp. 2488–2501, 2015.
S.-D. Wang, H.-M. Wang, W. Wang, and V. C. M. Leung, “Detecting intelligent jamming on physical broadcast channel in 5G NR,” IEEE Commun. Letters, vol. 27, no. 5, pp. 1292–1296, 2023.
D. Karagiannis and A. Argyriou, “Jamming attack detection in a pair of RF communicating vehicles using unsupervised machine learning,” Vehicular Communications, vol. 13, pp. 56–63, 2018.
M. R. Dey, M. Patra, and P. Mishra, “Efficient detection and localization of dos attacks in heterogeneous vehicular networks,” IEEE Trans. on Veh. Techn., vol. 72, no. 5, pp. 5597–5611, 2023.
S. Balakrishnan, P. Wang, A. Bhuyan, and Z. Sun, “Impact analysis of mobility on physical layer security of mmwave networks,” in Resilience Week, vol. 1. San Antonio, TX, U.S.A.: IEEE, Nov. 2019, pp. 163–168.
S. Malebary, W. Xu, and C.-T. Huang, “Jamming mobility in 802.11p networks: Modeling, evaluation, and detection,” in IEEE Int. Perf. Computing and Commun. Conf., Las Vegas, U.S.A, Dec 2016, pp. 1–7.
O. Punal, C. Pereira, A. Aguiar, and J. Gross, “Experimental characterization and modeling of rf jamming attacks on vanets,” IEEE Trans. on Vehic. Tech., vol. 64, no. 2, pp. 524–540, 2015.
H. Bouzabia, T. N. Do, and G. Kaddoum, “Deep learning-enabled deceptive jammer detection for low probability of intercept communications,” IEEE Systems Journal, vol. 17, no. 2, pp. 2166–2177, 2023.
S. Dinh-Van, T. M. Hoang, B. B. Cebecioglu, D. S. Fowler, Y. K. Mo, and M. D. Higgins, “A defensive strategy against beam training attack in 5g mmwave networks for manufacturing,” IEEE Trans. on Inf. Forensics and Security, vol. 18, pp. 2204–2217, 2023.
N. Venkata Abhishek and M. Gurusamy, “Jade: Low power jamming detection using machine learning in vehicular networks,” IEEE Wireless Commun. Letters, vol. 10, no. 10, pp. 2210–2214, 2021.
T. Cheng, P. Li, and S. Zhu, “An algorithm for jammer localization in wireless sensor networks,” in IEEE Int. Conf. on Advanced Inf. Net. and Applications, Washington, DC, U.S.A., Mar. 2012, pp. 724–731.
3GPP, “5G; NR; Base Station (BS) radio transmission and reception,” 3GPP, TS 38.104 version 16.4.0 Release 16, 2020. [Online]. Available: www.portal.3gpp.org
——, “5G; Study on channel model for frequencies from 0.5 to 100 GHz,” 3GPP, TR 38.901 version 16.1.0 Release 16, 2020. [Online]. Available: www.portal.3gpp.org
——, “5G; NR; User Equipment (UE) radio transmission and reception; Part 1: Range 1 Standalone,” 3GPP, TS 38.101-1 version 16.4.0 Release 16, 2020. [Online]. Available: www.portal.3gpp.org
——, “5G; NR; Packet Data Convergence Protocol (PDCP) specification,” 3GPP, TS 38.323 version 16.2.0 Release 16, 2020. [Online]. Available: www.portal.3gpp.org
X. Han, S. Liu, and L. Fu, “Hybrid beamforming for full-duplex enabled cellular system in the unlicensed mmwave band,” in 2021 IEEE Global Communications Conference (GLOBECOM). IEEE, 2021, pp. 1–6.
S. Won and S. W. Choi, “A tutorial on 3gpp initial cell search: Exploring a potential for intelligence based cell search,” IEEE Access, vol. 9, pp. 100 223–100 263, 2021.
3GPP, “5G; NR; Physical channels and modulation,” 3GPP, TS 38.211 version 16.2.0 Release 16, 2020. [Online]. Available: www.portal.3gpp.org