5G Network Slicing: Security Challenges, Attack Vectors, and Mitigation Approaches

This paper explores the security challenges associated with network slicing in 5th Generation (5G) networks, a technology that enables the creation of virtual networks tailored to different use cases. This study contributes to network slicing research efforts by providing a comprehensive classification of attacks aligned with the architectural layers of 5G, complemented by practical mitigation approaches suitable for multi-tenant environments. The classification depicts specific attacks and categorizes vulnerabilities across layers such as orchestration, virtualization, and inter-slice communication. Additionally, mitigation strategies are discussed, emphasizing the importance of real-time monitoring and robust access controls. The proposed classification aims to support the development of advanced security mechanisms, including risk assessment models and automated mitigation strategies, tailored to the dynamic and heterogeneous nature of 5G slicing. The findings highlight the need for layered defenses, AI-driven monitoring, and architectural isolation as critical components to enhance the resilience of 5G slicing deployments.

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Publication Details

Journal
Sensors
Published
2025-06-24
DOI
https://doi.org/10.3390/s25133940
Citations
11
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
16.36
Controls
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article

5G Network Slicing: Security Challenges, Attack Vectors, and Mitigation Approaches

Ricardo Santos, Silvestre Malta, Pedro Pinto, José Geraldo Dias
11 citations
Sensors
Software-Defined Networks and 5G
16.36
article

5G Network Slicing: Security Challenges, Attack Vectors, and Mitigation Approaches

Ricardo Santos, Silvestre Malta, Pedro Pinto, José Geraldo Dias
article en
11 citations

Abstract

This paper explores the security challenges associated with network slicing in 5th Generation (5G) networks, a technology that enables the creation of virtual networks tailored to different use cases. This study contributes to network slicing research efforts by providing a comprehensive classification of attacks aligned with the architectural layers of 5G, complemented by practical mitigation approaches suitable for multi-tenant environments. The classification depicts specific attacks and categorizes vulnerabilities across layers such as orchestration, virtualization, and inter-slice communication. Additionally, mitigation strategies are discussed, emphasizing the importance of real-time monitoring and robust access controls. The proposed classification aims to support the development of advanced security mechanisms, including risk assessment models and automated mitigation strategies, tailored to the dynamic and heterogeneous nature of 5G slicing. The findings highlight the need for layered defenses, AI-driven monitoring, and architectural isolation as critical components to enhance the resilience of 5G slicing deployments.

SensorsVol. 25(13)
Universidade Politécnica de Viana do Castelo (PT), Polytechnic Institute of Porto (PT)
Openalex Percentile: Top 1%
Software-Defined Networks and 5G
16.36
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