Detail publikačního výsledku

Enhancing fiber security using a simple state of polarization analyzer and machine learning

TOMAŠOV, A.; DEJDAR, P.; MÜNSTER, P.; HORVÁTH, T.; BARCÍK, P.; DA ROS, F.

Original Title

Enhancing fiber security using a simple state of polarization analyzer and machine learning

English Title

Enhancing fiber security using a simple state of polarization analyzer and machine learning

Type

WoS Article

Original Abstract

The paper focuses on the security of fiber-optic cable infrastructures by detecting vibrations using an optical state of polarization analyzer. The developed system can detect various security breaches. The system only detects abnormal events without any event classification. The proposed system relies on an analyzer evaluating optical polarization differences caused by mechanical or acoustic vibrations analyzed by a machine-learning model for real-time anomaly detection. The main goal of experiments is to find the best combination of the normalization method and anomaly detector. The proposed system achieves an F1-score over 95.65%, which proves the solution’s suitability for protecting fiber-optic infrastructures.

English abstract

The paper focuses on the security of fiber-optic cable infrastructures by detecting vibrations using an optical state of polarization analyzer. The developed system can detect various security breaches. The system only detects abnormal events without any event classification. The proposed system relies on an analyzer evaluating optical polarization differences caused by mechanical or acoustic vibrations analyzed by a machine-learning model for real-time anomaly detection. The main goal of experiments is to find the best combination of the normalization method and anomaly detector. The proposed system achieves an F1-score over 95.65%, which proves the solution’s suitability for protecting fiber-optic infrastructures.

Keywords

Communication system security;Machine learning;Neural networks;Optical sensor;Optical polarization

Key words in English

Communication system security;Machine learning;Neural networks;Optical sensor;Optical polarization

Authors

TOMAŠOV, A.; DEJDAR, P.; MÜNSTER, P.; HORVÁTH, T.; BARCÍK, P.; DA ROS, F.

RIV year

2024

Released

10.06.2023

Publisher

Elsevier Ltd.

ISBN

1879-2545

Periodical

OPTICS AND LASER TECHNOLOGY

Volume

167

Number

2023

State

United Kingdom of Great Britain and Northern Ireland

Pages count

9

URL

https://www.sciencedirect.com/science/article/pii/S0030399223005613

Full text in the Digital Library

http://hdl.handle.net/

BibTex

@article{BUT183730,
  author="Adrián {Tomašov} and Petr {Dejdar} and Petr {Münster} and Tomáš {Horváth} and Peter {Barcík} and Francesco {Da Ros}",
  title="Enhancing fiber security using a simple state of polarization analyzer and machine learning",
  journal="OPTICS AND LASER TECHNOLOGY",
  year="2023",
  volume="167",
  number="2023",
  pages="9",
  doi="10.1016/j.optlastec.2023.109668",
  issn="0030-3992",
  url="https://www.sciencedirect.com/science/article/pii/S0030399223005613"
}