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Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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Source code of Ultra-Low Latency User-Plane Cyberattack Detection in SDN-based Smart Grids

Authors: Akem Aristide;

Source code of Ultra-Low Latency User-Plane Cyberattack Detection in SDN-based Smart Grids

Abstract

Ultra-Low Latency User-Plane Cyberattack Detection in SDN-based Smart Grids This repository contains the public version of the code for our work on cyberattack detection in SDN-based smart grids at line rate leveraging user-plane inference. The paper was presented at the ACM SIGEnergy Workshop on the Security and Privacy of Energy Systems (EnergySP), co-located with the 15th ACM International Conference on Future and Sustainable Energy Systems (e-Energy), Singapore, 4 June 2024. We show that by leveraging user-plane inference on a per-packet basis, we can accurately and rapidly detect and mitigate cyberattacks on smart grid networks in real time. For details, please check out our paper.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average