GPON Traffic Analysis with TensorFlow
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137433" target="_blank" >RIV/00216305:26220/20:PU137433 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9163575" target="_blank" >https://ieeexplore.ieee.org/document/9163575</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP49548.2020.9163575" target="_blank" >10.1109/TSP49548.2020.9163575</a>
Alternative languages
Result language
angličtina
Original language name
GPON Traffic Analysis with TensorFlow
Original language description
The paper presents the latest research results of gigabit passive optical network analysis using machine learning algorithms. TensorFlow has been used to learn the frames of GPON management traffic of the G.984.3 protocol and detect outliers to the standard. The frames are captured by FPGA programmable network card and processed with a software parser and further processed with the TensorFlow using JSON format. The proposed technique can bring a way how to test if vendors of network devices follow the standard and if the content of the frames can be treated as secure and trustworthy.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
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)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 43rd International Conference on Telecommunications and Signal Processing (TSP)
ISBN
978-1-7281-6376-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
69-72
Publisher name
IEEE
Place of publication
Milan, Italy
Event location
Milan, Italy
Event date
Jul 7, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000577106400016