With the rise of 5G and Internet of things, especially the key technology of 5G, network slice cuts a physical network into multiple virtual end-to-end networks, each of them can obtain logically independent network resources to support richer services. 5G mobile data and sensor data converge to form a growing network traffic. Traffic explosion evolved into a mixed network type, and network viruses, worms, network theft and malicious attacks are also involved. How to distinguish traffic types, block malicious traffic and make effective use of sensor data under the background of 5G network slice, and also the significance of this study.

中文翻译：

---

基于机器学习的5G网络切片流量分析

随着5G和物联网（尤其是5G的关键技术）的兴起，网络切片将一个物理网络切成多个虚拟的端到端网络，它们中的每一个都可以获取逻辑上独立的网络资源来支持更丰富的服务。5G移动数据和传感器数据融合以形成不断增长的网络流量。流量爆炸演变为混合网络类型，并且还涉及网络病毒，蠕虫，网络盗窃和恶意攻击。在5G网络切片的背景下如何区分流量类型，阻止恶意流量并有效利用传感器数据，这也是本研究的重要意义。