Experimental Analysis of Adaptive ML Classifiers for Dynamic Detection of Emerging Physical-Layer Attacks
Paper i proceeding, 2025
We experimentally evaluate three ML classifiers for detecting physical-layer attacks in optical networks. Using telemetry data from a real-world testbed under six attack types, we achieve Balanced Accuracy of up to 0.936 for unseen attacks, and demonstrate rapid adaptation of Multilayer Perceptron to evolving threats.
attack detection
data stream
machine learning
Författare
Aleksandra Knapinska
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Politechnika Wrocławska
Marija Furdek Prekratic
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
European Conference on Optical Communication, ECOC
51st European Conference on Optical Communication (ECOC 2025)
Copenhagen, Denmark,
Copenhagen, Denmark,
5G betrodda och säkra nätverkstjänster (5G-TACTIC)
Europeiska kommissionen (EU) (EC/H2020/101127973), 2023-12-01 -- 2026-11-30.
Styrkeområden
Informations- och kommunikationsteknik
Ämneskategorier (SSIF 2025)
Kommunikationssystem
Datavetenskap (datalogi)
Datorsystem