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Detail publikace
TOMAŠOV, A. DEJDAR, P. MÜNSTER, P. HORVÁTH, T. BARCÍK, P. DA ROS, F.
Originální název
Enhancing fiber security using a simple state of polarization analyzer and machine learning
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Communication system security;Machine learning;Neural networks;Optical sensor;Optical polarization
Autoři
TOMAŠOV, A.; DEJDAR, P.; MÜNSTER, P.; HORVÁTH, T.; BARCÍK, P.; DA ROS, F.
Vydáno
10. 6. 2023
Nakladatel
Elsevier Ltd.
ISSN
1879-2545
Periodikum
OPTICS AND LASER TECHNOLOGY
Ročník
167
Číslo
2023
Stát
Spojené království Velké Británie a Severního Irska
Strany počet
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" }