Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives
The convergence of 5G and Wi-Fi networks has become a cornerstone of next-generation communication systems, offering seamless connectivity, improved performance, and diversified use cases. However, this integration introduces unique security challenges, particularly in the context of intrusion detec...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10906593/ |
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| author | Cherifa Hamroun Anne Fladenmuller Michel Pariente Guy Pujolle |
| author_facet | Cherifa Hamroun Anne Fladenmuller Michel Pariente Guy Pujolle |
| author_sort | Cherifa Hamroun |
| collection | DOAJ |
| description | The convergence of 5G and Wi-Fi networks has become a cornerstone of next-generation communication systems, offering seamless connectivity, improved performance, and diversified use cases. However, this integration introduces unique security challenges, particularly in the context of intrusion detection systems. This survey explores the threats and vulnerabilities inherent in 5G and Wi-Fi access networks, highlighting the need for customized intrusion detection solutions in these environments. In addition, we present the various types and architectures of intrusion detection systems, the existing datasets used to evaluate their performance, and the recent detection methods that accurately identify the presence or absence of an attack. Furthermore, the paper provides a comprehensive overview of state-of-the-art studies, positioning them within current 5G/Wi-Fi architectures. Finally, we highlight the key architectural differences and conclude by discussing the implications of 5G/Wi-Fi architectural convergence in the development of future intrusion detection systems. This convergence raises crucial concerns about the integration of security mechanisms in a unified ecosystem. Hence, this work aims to serve as a foundation for future research on robust and scalable detection mechanisms in converged 5G/Wi-Fi networks. |
| format | Article |
| id | doaj-art-faeba181b5e94768b4cd2429c6e4887e |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-faeba181b5e94768b4cd2429c6e4887e2025-08-20T02:58:18ZengIEEEIEEE Access2169-35362025-01-0113409504097610.1109/ACCESS.2025.354633810906593Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and PerspectivesCherifa Hamroun0https://orcid.org/0000-0003-3611-7174Anne Fladenmuller1Michel Pariente2Guy Pujolle3Computer Laboratory of Paris 6 (LIP6), Sorbonne University, Paris, FranceComputer Laboratory of Paris 6 (LIP6), Sorbonne University, Paris, FranceMETEOR Network, Rungis, FranceComputer Laboratory of Paris 6 (LIP6), Sorbonne University, Paris, FranceThe convergence of 5G and Wi-Fi networks has become a cornerstone of next-generation communication systems, offering seamless connectivity, improved performance, and diversified use cases. However, this integration introduces unique security challenges, particularly in the context of intrusion detection systems. This survey explores the threats and vulnerabilities inherent in 5G and Wi-Fi access networks, highlighting the need for customized intrusion detection solutions in these environments. In addition, we present the various types and architectures of intrusion detection systems, the existing datasets used to evaluate their performance, and the recent detection methods that accurately identify the presence or absence of an attack. Furthermore, the paper provides a comprehensive overview of state-of-the-art studies, positioning them within current 5G/Wi-Fi architectures. Finally, we highlight the key architectural differences and conclude by discussing the implications of 5G/Wi-Fi architectural convergence in the development of future intrusion detection systems. This convergence raises crucial concerns about the integration of security mechanisms in a unified ecosystem. Hence, this work aims to serve as a foundation for future research on robust and scalable detection mechanisms in converged 5G/Wi-Fi networks.https://ieeexplore.ieee.org/document/10906593/5Garchitecturesconvergenceintrusion detection systemsmachine learningrules |
| spellingShingle | Cherifa Hamroun Anne Fladenmuller Michel Pariente Guy Pujolle Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives IEEE Access 5G architectures convergence intrusion detection systems machine learning rules |
| title | Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives |
| title_full | Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives |
| title_fullStr | Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives |
| title_full_unstemmed | Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives |
| title_short | Intrusion Detection in 5G and Wi-Fi Networks: A Survey of Current Methods, Challenges, and Perspectives |
| title_sort | intrusion detection in 5g and wi fi networks a survey of current methods challenges and perspectives |
| topic | 5G architectures convergence intrusion detection systems machine learning rules |
| url | https://ieeexplore.ieee.org/document/10906593/ |
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