Insight of Anomaly Detection with NWDAF in 5G

Yachao Yuan, Christian Gehrmann, Jakob Sternby, Luis Barriga
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引用次数: 3

Abstract

Data analytics is regarded as an important function of 5G networks. The Network Data Analytics Function (NWDAF) is standardized in 3GPP to enhance 5G network performance by analyzing data from network functions and user equipment. Abnormal behavior detection, which is part of the NWDAF framework, has the potential to be a powerful tool to improve 5G network security. Despite this, only limited research has been conducted in the area so far. This paper explains abnormal behavior detection in NWDAF specified in 3GPP. Furthermore, we extensively review the related work and summarize open problems and provide possible future research directions.
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5G环境下NWDAF异常检测的洞察
数据分析被认为是5G网络的重要功能。网络数据分析功能(NWDAF)是3GPP标准,通过分析网络功能和用户设备的数据,提高5G网络性能。异常行为检测是NWDAF框架的一部分,有可能成为提高5G网络安全性的有力工具。尽管如此,到目前为止,在该领域只进行了有限的研究。本文阐述了3GPP中NWDAF的异常行为检测。此外,我们还对相关工作进行了广泛的回顾,总结了存在的问题,并提出了未来可能的研究方向。
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