Detail publikace

GPON Traffic Analysis with TensorFlow

OUJEZSKÝ, V. TOMAŠOV, A. HOLÍK, M. ŠKORPIL, V. HORVÁTH, T. JURČÍK, M.

Originální název

GPON Traffic Analysis with TensorFlow

Anglický název

GPON Traffic Analysis with TensorFlow

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

BibTex


@inproceedings{BUT165542,
  author="Václav {Oujezský} and Adrián {Tomašov} and Martin {Holík} and Vladislav {Škorpil} and Tomáš {Horváth} and Michal {Jurčík}",
  title="GPON Traffic Analysis with TensorFlow",
  annote="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.",
  address="IEEE",
  booktitle="2020 43rd International Conference on Telecommunications and Signal Processing (TSP)",
  chapter="165542",
  doi="10.1109/TSP49548.2020.9163575",
  howpublished="online",
  institution="IEEE",
  year="2020",
  month="july",
  pages="69--72",
  publisher="IEEE",
  type="conference paper"
}