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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2507.20873 |
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| _version_ | 1866915414612639744 |
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| author | Ha, Song Son Foerster, Florian Doebbert, Thomas Robert Kittel, Tim Merli, Dominik Scholl, Gerd |
| author_facet | Ha, Song Son Foerster, Florian Doebbert, Thomas Robert Kittel, Tim Merli, Dominik Scholl, Gerd |
| contents | In the era of Industry 4.0, the growing need for secure and efficient communication systems has driven the development of fifth-generation (5G) networks characterized by extremely low latency, massive device connectivity and high data transfer speeds. However, the deployment of 5G networks presents significant security challenges, requiring advanced and robust solutions to counter increasingly sophisticated cyber threats. This paper proposes a testbed and software architecture to strengthen the security of Private 5G Networks, particularly in industrial communication environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_20873 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Testbed and Software Architecture for Enhancing Security in Industrial Private 5G Networks Ha, Song Son Foerster, Florian Doebbert, Thomas Robert Kittel, Tim Merli, Dominik Scholl, Gerd Cryptography and Security Machine Learning In the era of Industry 4.0, the growing need for secure and efficient communication systems has driven the development of fifth-generation (5G) networks characterized by extremely low latency, massive device connectivity and high data transfer speeds. However, the deployment of 5G networks presents significant security challenges, requiring advanced and robust solutions to counter increasingly sophisticated cyber threats. This paper proposes a testbed and software architecture to strengthen the security of Private 5G Networks, particularly in industrial communication environments. |
| title | Testbed and Software Architecture for Enhancing Security in Industrial Private 5G Networks |
| topic | Cryptography and Security Machine Learning |
| url | https://arxiv.org/abs/2507.20873 |