GPON PLOAMd Message Analysis Using Supervised Neural Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137814" target="_blank" >RIV/00216305:26220/20:PU137814 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2076-3417/10/22/8139/htm" target="_blank" >https://www.mdpi.com/2076-3417/10/22/8139/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app10228139" target="_blank" >10.3390/app10228139</a>

Result language
angličtina
Original language name
GPON PLOAMd Message Analysis Using Supervised Neural Networks
Original language description
This paper discusses the possibility of analyzing the orchestration protocol used in gigabit-capable passive optical networks (GPONs). Considering the fact that a GPON is defined by the International Telecommunication Union Telecommunication sector (ITU-T) as a set of recommendations, implementation across device vendors might exhibit few differences, which complicates analysis of such protocols. Therefore, machine learning techniques are used (e.g., neural networks) to evaluate differences in GPONs among various device vendors. As a result, this paper compares three neural network models based on different types of recurrent cells and discusses their suitability for such analysis.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20203 - Telecommunications

Project
<a href="/en/project/VI20192022135" target="_blank" >VI20192022135: Deep hardware detection of network traffic of next generation passive optical network in critical infrastructures</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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