3 papers
eess.SP2024
Detecting 5G Narrowband Jammers with CNN, k-nearest Neighbors, and Support Vector Machines
Matteo Varotto, Florian Heinrichs, Timo Schuerg +2
5G cellular networks are particularly vulnerable against narrowband jammers that target specific control sub-channels in the radio signal. One mitigation approach is to detect such…
eess.SP2024
Detecting 5G Signal Jammers Using Spectrograms with Supervised and Unsupervised Learning
Matteo Varotto, Stefan Valentin, Stefano Tomasin
Cellular networks are potential targets of jamming attacks to disrupt wireless communications. Since the fifth generation (5G) of cellular networks enables mission-critical applica…
eess.SP2024
One-Class Classification as GLRT for Jamming Detection in Private 5G Networks
Matteo Varotto, Stefan Valentin, Francesco Ardizzon +2
5G mobile networks are vulnerable to jamming attacks that may jeopardize valuable applications such as industry automation. In this paper, we propose to analyze radio signals with…