A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response.

Sun C, Zhang W, Sun P, Wang H, Yang C

DOI: 10.3390/s25103208
Published: 2025 May 20
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.3390/s25103208,
  title = {A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response.},
  author = {Sun C and Zhang W and Sun P and Wang H and Yang C},
  year = {2025},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s25103208},
  url = {https://doi.org/10.3390/s25103208}
}

RIS

TY  - JOUR
TI  - A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response.
AU  - Sun C
AU  - Zhang W
AU  - Sun P
AU  - Wang H
AU  - Yang C
PY  - 2025
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s25103208
UR  - https://doi.org/10.3390/s25103208
ER  -

APA

C, S., W, Z., P, S., H, W., & C, Y. (2025). A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s25103208

Source records

pubmed · retrieved 2026-09-26T10:26:43.736Z