Detail publikace

Deploying Machine Learning in Distributed Sensing to Increase Resilience of Fiber Optic Infrastructure

MÜNSTER, P. TOMAŠOV, A. DEJDAR, P. HORVÁTH, T.

Originální název

Deploying Machine Learning in Distributed Sensing to Increase Resilience of Fiber Optic Infrastructure

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

We report a novel approach to the security of fiber optic infrastructures utilizing state of polarization analyzes or Mach-Zehnder interferometry and using supervised or unsupervised machine-learning models for unauthorized cable manipulation detection.

Klíčová slova

Fiber optic communications;Mach Zehnder interferometers;Neural networks;Optical networks;Phase modulation;Polarization

Autoři

MÜNSTER, P.; TOMAŠOV, A.; DEJDAR, P.; HORVÁTH, T.

Vydáno

7. 5. 2023

Nakladatel

Optica Publishing Group

Místo

San Jose, CA, USA

ISBN

978-1-957171-25-8

Kniha

2023 Conference on Lasers and Electro-Optics (CLEO)

Strany počet

2

URL

https://opg.optica.org/abstract.cfm?uri=CLEO_SI-2023-JW2A.102

BibTex

@inproceedings{BUT184183,
  author="Petr {Münster} and Adrián {Tomašov} and Petr {Dejdar} and Tomáš {Horváth}",
  title="Deploying Machine Learning in Distributed Sensing to Increase Resilience of Fiber Optic Infrastructure",
  booktitle="2023 Conference on Lasers and Electro-Optics (CLEO)",
  year="2023",
  pages="2",
  publisher="Optica Publishing Group",
  address="San Jose, CA, USA",
  isbn="978-1-957171-25-8",
  url="https://opg.optica.org/abstract.cfm?uri=CLEO_SI-2023-JW2A.102"
}