论文标题
5G网络安全中的人工智能和机器学习：机会，优势和未来的研究趋势
Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends
论文作者
论文摘要
5G网络中的最新技术和建筑进步已证明它们的价值是在世界范围内开始的。访问核心网络的关键性能提升因子是软件化，云化和启用网络功能的虚拟化。随着计划计划利用它的人，系统中的风险，威胁和脆弱性也带来了风险，威胁和脆弱性。因此，确保傻瓜端到端（E2E）安全成为至关重要的问题。人工智能（AI）和机器学习（ML）可以在设计，建模和自动化有效的安全协议中起着至关重要的作用，以应对各种威胁和广泛的威胁。 AI和ML已经证明了它们在不同领域的有效性，以较高的精度进行分类，识别和自动化。由于5G Networks的主要销售点是较高的数据速率和速度，因此很难使用典型/传统的保护措施从不同点处理广泛的威胁。因此，AI和ML可以在保护高度数据驱动的软件和虚拟化网络组件中发挥核心作用。本文介绍了5G网络安全性的AI和ML驱动的应用程序，其含义和可能的研究方向。此外，讨论了5G体系结构中的关键数据收集点的概述，以进行威胁分类和异常检测。
Recent technological and architectural advancements in 5G networks have proven their worth as the deployment has started over the world. Key performance elevating factor from access to core network are softwareization, cloudification and virtualization of key enabling network functions. Along with the rapid evolution comes the risks, threats and vulnerabilities in the system for those who plan to exploit it. Therefore, ensuring fool proof end-to-end (E2E) security becomes a vital concern. Artificial intelligence (AI) and machine learning (ML) can play vital role in design, modelling and automation of efficient security protocols against diverse and wide range of threats. AI and ML has already proven their effectiveness in different fields for classification, identification and automation with higher accuracy. As 5G networks' primary selling point has been higher data rates and speed, it will be difficult to tackle wide range of threats from different points using typical/traditional protective measures. Therefore, AI and ML can play central role in protecting highly data-driven softwareized and virtualized network components. This article presents AI and ML driven applications for 5G network security, their implications and possible research directions. Also, an overview of key data collection points in 5G architecture for threat classification and anomaly detection are discussed.
