Sec5GLoc: Securing 5G Indoor Localization via Adversary-Resilient Deep Learning Architecture

Ildi Alla, Valeria Loscri

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DOI: 10.1109/cns66487.2025.11194175
Published: 2025-09-08
Container: 2025 IEEE Conference on Communications and Network Security (CNS)
Publisher: IEEE
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1109/cns66487.2025.11194175,
  title = {Sec5GLoc: Securing 5G Indoor Localization via Adversary-Resilient Deep Learning Architecture},
  author = {Ildi Alla and Valeria Loscri},
  year = {2025},
  journal = {2025 IEEE Conference on Communications and Network Security (CNS)},
  doi = {10.1109/cns66487.2025.11194175},
  url = {https://doi.org/10.1109/cns66487.2025.11194175}
}

RIS

TY  - JOUR
TI  - Sec5GLoc: Securing 5G Indoor Localization via Adversary-Resilient Deep Learning Architecture
AU  - Ildi Alla
AU  - Valeria Loscri
PY  - 2025
JO  - 2025 IEEE Conference on Communications and Network Security (CNS)
DO  - 10.1109/cns66487.2025.11194175
UR  - https://doi.org/10.1109/cns66487.2025.11194175
ER  -

APA

Alla, I., & Loscri, V. (2025). Sec5GLoc: Securing 5G Indoor Localization via Adversary-Resilient Deep Learning Architecture. 2025 IEEE Conference on Communications and Network Security (CNS). https://doi.org/10.1109/cns66487.2025.11194175

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crossref · retrieved 2026-09-26T03:35:30.583Z