A Unified Siamese Learning Framework for Zero-Day Anomaly Detection and Classification in Optical Networks
Paper i proceeding, 2025
A multi-similarity Siamese neural network unifies zero-day anomaly detection and one-shot classification in optical networks, achieving over 99% accuracy and instant adaptability across lightpaths and unseen anomaly types without any retraining.
Anomaly detection
Contrastive learning
Artificial intelligence
Anomaly classification
Machine learning
Optical networks
Författare
Carlos Natalino Da Silva
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Flávia Pessoa Monteiro
Federal University of Western Pará (UFOPA)
Paolo Monti
Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk
Proceedings of the Optical Fiber Communication Conference (OFC) 2026
M3A
Optical Fiber Communication Conference (OFC) 2026
Los Angeles, CA, USA,
Los Angeles, CA, USA,
Styrkeområden
Informations- och kommunikationsteknik
Ämneskategorier (SSIF 2025)
Kommunikationssystem
Datavetenskap (datalogi)
Telekommunikation
Relaterade dataset
Optical network soft failure dataset [dataset]
URI: https://data.mendeley.com/datasets/y3pspy7j83/1 DOI: 10.17632/y3pspy7j83.1