Utilizing a State of Polarization Change Detector and Machine Learning for Enhanced Security in Fiber-Optic Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU152064" target="_blank" >RIV/00216305:26220/24:PU152064 - isvavai.cz</a>

Result on the web

<a href="https://opg.optica.org/abstract.cfm?uri=CLEO_AT-2024-JTu2A.217" target="_blank" >https://opg.optica.org/abstract.cfm?uri=CLEO_AT-2024-JTu2A.217</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1364/CLEO_AT.2024.JTu2A.217" target="_blank" >10.1364/CLEO_AT.2024.JTu2A.217</a>

Result language

angličtina

Original language name

Utilizing a State of Polarization Change Detector and Machine Learning for Enhanced Security in Fiber-Optic Networks

Original language description

The paper presents a novel method for securing fiber-optic infrastructures using a state of polarization analyzer combined with machine learning algorithms. The proposed system detects vibrations indicative of security breaches, achieving an F1-score above 95.65 %.}

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20203 - Telecommunications

Project

<a href="/en/project/VJ01010035" target="_blank" >VJ01010035: Security risks of photonic communication networks</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

CLEO: Applications and Technology 2024

ISBN

978-1-957171-39-5

ISSN

—

e-ISSN

—

Number of pages

2

Pages from-to

„“-„“

Publisher name

Optica Publishing Group

Place of publication

neuveden

Event location

Charlotte, North Carolina United States

Event date

May 5, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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