  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.
