Smart Jamming Attacks in 5G New Radio: A Review
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Abstract (arXiv)
The fifth generation of wireless cellular networks (5G) is expected to be the infrastructure for emergency services, natural disasters rescue, public safety, and military communications. 5G, as any previous wireless cellular network, is vulnerable to jamming attacks, which create deliberate interference to hinder the communication of legitimate users. Therefore, jamming 5G networks can be a real threat to public safety. Thus, there is a strong need to investigate to what extent these networks are vulnerable to jamming attacks. For this investigation, we consider the 3GPP standard released in 2017, which is widely accepted as the primary reference for the deployment of these networks. First, we describe the key elements of 5G New Radio (NR) architecture, such as different channels and signals exchanged between the base station and user equipment. Second, we conduct an in-depth review of the jamming attack models and we assess the 5G NR vulnerabilities to these jamming attacks. Then, we present the state-of-the-art detection and mitigation techniques, and we discuss their suitability to defeat smart jammers in 5G wireless networks. Finally, we provide some recommendations and future research directions at the end of this paper.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Sep 2020.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 2.
4 papers.
- 2024DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVscited by 2
- 2025On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directionscited by 2
- 2025A Two-Stage CAE-Based Federated Learning Framework for Efficient Jamming Detection in 5G Networkscited by 1
- 2022Multi-Agent Adversarial Attacks for Multi-Channel Communicationscited by 0
- 2025On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions19 Aug 2025
- 2025A Two-Stage CAE-Based Federated Learning Framework for Efficient Jamming Detection in 5G Networks25 Jan 2025
- 2024DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVs5 Mar 2024
- 2022Multi-Agent Adversarial Attacks for Multi-Channel Communications22 Jan 2022