An open testbed for O-RAN experimentation with AI-enabled control and monitoring


Por: Parada, R, Vilajosana, X, Alfayoumi, S, Serra, J, Font-Bach, O, Dini, P

Publicada: 1 sep 2025 Ahead of Print: 1 ago 2025
Resumen:
The proliferation of open radio access networks (O-RAN) in modern 5G systems has ushered in enhanced flexibility and efficiency, but it has also introduced novel security challenges. In response, this paper presents a novel AI-based anomaly detection framework tailored for O-RAN networks operating in 5G environments. By employing principal component analysis for dimensionality reduction and a deep neural network for classification, the proposed system efficiently processes large-scale 5G traffic data while achieving high detection accuracy and low latency. Experimental evaluation on an open-source testbed with realistic cellular traffic demonstrates rapid convergence, with both training and validation accuracy values approaching 100% and effective detection of anomalies introduced via user equipment identifier swaps. The testbed processed over 300,000 traffic samples with 31 distinct network features, emulating 8 unique user equipment profiles under diverse radio conditions. Under adversarial scenarios, such as identity-swapping attacks, the system identified anomalous behavior with detection rates exceeding 40%, while maintaining a near-zero false positive rate on clean traffic. These results underscore the testbed's capability to simulate complex 5G environments and the framework's ability to deliver highly accurate, low-latency, and scalable anomaly detection. Overall, this work highlights the potential of advanced AI techniques to significantly enhance the security and resilience of modern wireless communication networks.

Filiaciones:
Parada, R:
 CERCA, Ctr Tecnol Telecommun Catalunya CTTC, Av Carl Friedrich Gauss 7, Barcelona 08860, Catalonia, Spain

Vilajosana, X:
 Univ Oberta Catalunya UOC, EHlth Ctr, Rambla Poblenou,156, Barcelona 08018, Catalonia, Spain

Alfayoumi, S:
 Worldsensing SL, Carrer Viriat,47, Barcelona 08014, Catalonia, Spain

Serra, J:
 CERCA, Ctr Tecnol Telecommun Catalunya CTTC, Av Carl Friedrich Gauss 7, Barcelona 08860, Catalonia, Spain

Font-Bach, O:
 Software Radio Syst SRS, Carrer Pujades,77-79, Barcelona 08005, Catalonia, Spain

Dini, P:
 CERCA, Ctr Tecnol Telecommun Catalunya CTTC, Av Carl Friedrich Gauss 7, Barcelona 08860, Catalonia, Spain

Centre Tecnològic de Telecomunicacions de Catalunya, Castelldefels, Spain
Universitat Oberta de Catalunya, eHealth Center, Barcelona, Spain
Worldsensing SL, Barcelona, Spain
Software Radio Systems (SRS), Barcelona, Spain
ISSN: 25431536





Internet of Things
Editorial
ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, Países Bajos
Tipo de documento: Article
Volumen: 33 Número:
Páginas:
WOS Id: 001561234200001
imagen hybrid, All Open Access; Hybrid Gold Open Access

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