# 5G NR Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation

arXiv: https://arxiv.org/abs/1803.03845 · HTML: https://mlsanity.com/paper/1803.03845/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Mar 2018.

## Built on by (most cited first, 5 of 5)

- [Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples](https://mlsanity.com/paper/2207.01531/) (2022)
- [The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining](https://mlsanity.com/paper/2202.08185/) (2022)
- [DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVs](https://mlsanity.com/paper/2403.02645/) (2024)
- [Linear Jamming Bandits: Sample-Efficient Learning for Non-Coherent Digital Jamming](https://mlsanity.com/paper/2207.02365/) (2022)
- [Explainable and Hardware-Efficient Jamming Detection for 5G Networks Using the Convolutional Tsetlin Machine](https://mlsanity.com/paper/2603.07336/) (2026)

## Abstract (arXiv)

In December 2017, the Third Generation Partnership Project (3GPP) released the first set of specifications for 5G New Radio (NR), which is currently the most widely accepted 5G cellular standard. 5G NR is expected to replace LTE and previous generations of cellular technology over the next several years, providing higher throughput, lower latency, and a host of new features. Similar to LTE, the 5G NR physical layer consists of several physical channels and signals, most of which are vital to the operation of the network. Unfortunately, like for any wireless technology, disruption through radio jamming is possible. This paper investigates the extent to which 5G NR is vulnerable to jamming and spoofing, by analyzing the physical downlink and uplink control channels and signals. We identify the weakest links in the 5G NR frame, and propose mitigation strategies that should be taken into account during implementation of 5G NR chipsets and base stations.