Published February 2, 2026 | Version v1.0
Software Open

Source code of Encrypted Traffic Classification at Line Rate in Programmable Switches with Machine Learning

  • 1. University of Oxford
  • 2. Orange

Description

Encrypted Traffic Classification at Line Rate in Programmable Switches with Machine Learning.
This repository contains the source code for our work on Encrypted Traffic Classification (ETC) in programmable switches with P4 and Machine Learning, appearing in the Proceedings of IEEE/IFIP NOMS 2024, 6–10 May 2024, Seoul, South Korea, and in the International Journal of Network Management, Wiley, vol. 35, no. 1, January 2025.

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nds-group/ETC_NOMS_2024-v1.0.zip

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Additional details

Related works

Is documented by
Journal article: 10.1002/nem.2320 (DOI)
Is supplement to
Software: https://github.com/nds-group/ETC_NOMS_2024/tree/v1.0 (URL)

Funding

European Commission
ORIGAMI - Optimized resource integration and global architecture for mobile infrastructure for 6G 101139270