In this work we demonstrate the integration of P4 enabled switches with high level AI techniques with the aim to improve efficiency and performance of DDoS detection and mitigation. Powerful ML-based strategies are adopted only when a suspicious behaviour is occurring in the network, and its activation is triggered by a coarser-grained and lightweight strategy fully executable in the data plane.

AL SADI, A., Savi, M., Berardi, D., Melis, A., Prandini, M., Callegati, F. (2023). Real-time Pipeline Reconfiguration of P4 Programmable Switches to Efficiently Detect and Mitigate DDoS Attacks. In Proceedings of the 26th Conference on Innovation in Clouds, Internet and Networks, ICIN 2023 (pp.21-23). IEEE [10.1109/ICIN56760.2023.10073501].

Real-time Pipeline Reconfiguration of P4 Programmable Switches to Efficiently Detect and Mitigate DDoS Attacks

Al Sadi Amir;Savi Marco;
2023

Abstract

In this work we demonstrate the integration of P4 enabled switches with high level AI techniques with the aim to improve efficiency and performance of DDoS detection and mitigation. Powerful ML-based strategies are adopted only when a suspicious behaviour is occurring in the network, and its activation is triggered by a coarser-grained and lightweight strategy fully executable in the data plane.
paper
P4, Programmable Data Planes, DDoS, Pipeline Reconfiguration
English
26th Conference on Innovation in Clouds, Internet and Networks, ICIN 2023 - 6 March 2023 through 9 March 2023
2023
Lopez, D; Montpetit, MJ; Cerroni, W; Di Mauro, M; Borylo, P
Proceedings of the 26th Conference on Innovation in Clouds, Internet and Networks, ICIN 2023
979-8-3503-9804-5
22-mar-2023
2023
21
23
10073501
https://ieeexplore.ieee.org/document/10073501
open
AL SADI, A., Savi, M., Berardi, D., Melis, A., Prandini, M., Callegati, F. (2023). Real-time Pipeline Reconfiguration of P4 Programmable Switches to Efficiently Detect and Mitigate DDoS Attacks. In Proceedings of the 26th Conference on Innovation in Clouds, Internet and Networks, ICIN 2023 (pp.21-23). IEEE [10.1109/ICIN56760.2023.10073501].
File in questo prodotto:
File Dimensione Formato  
Al Sadi-2023-ICIN-preprint.pdf

accesso aperto

Descrizione: Conference Paper
Tipologia di allegato: Submitted Version (Pre-print)
Licenza: Altro
Dimensione 159.61 kB
Formato Adobe PDF
159.61 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/410973
Citazioni
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
Social impact