Přístupnostní navigace
E-application
Search Search Close
Publication detail
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
Type
journal article in Web of Science
Language
English
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.
Keywords
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.
Released
10. 6. 2023
Publisher
Elsevier Ltd.
ISBN
1879-2545
Periodical
OPTICS AND LASER TECHNOLOGY
Year of study
167
Number
2023
State
United Kingdom of Great Britain and Northern Ireland
Pages count
9
URL
https://www.sciencedirect.com/science/article/pii/S0030399223005613
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="1879-2545", url="https://www.sciencedirect.com/science/article/pii/S0030399223005613" }