Multi-domain anomaly detection in a 5G network

2025/06/04 by Thomas Hoger, Hoger, Thomas, Philippe Owezarski +1
Computer Science · Engineering · #Anomaly Detection Techniques and Applications #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Network Security and Intrusion Detection #Networking and Internet Architecture (cs.NI) #Smart Grid Security and Resilience

paper · pdf · doi:10.48550/arxiv.2506.12070

openalex publication_date 2025/06/04 · openalex created_date 2025/10/08 · openalex updated_date 2026/07/28

Abstract

With the advent of 5G, mobile networks are becoming more dynamic and will therefore present a wider attack surface. To secure these new systems, we propose a multi-domain anomaly detection method that is distinguished by the study of traffic correlation on three dimensions: temporal by analyzing message sequences, semantic by abstracting the parameters these messages contain, and topological by linking them in the form of a graph. Unlike traditional approaches, which are limited to considering these domains independently, our method studies their correlations to obtain a global, coherent and explainable view of anomalies.

Citations

• Malicious Lateral Movement in 5G Core With Network Slicing And Its Detection
• Machine Learning based Anomaly Detection for 5G Networks
• Neural Message Passing for Quantum Chemistry
• Enriching Word Vectors with Subword Information
• Efficient Estimation of Word Representations in Vector Space
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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