Modeling for Malicious Traffic Detection in 6G Next Generation Networks

Abstract

Based on the digitalization of the world and the increasing use of data, we can say that the next ten years will see a huge leap in the use of data in virtualization, automation, health and more. One of the infrastructures to reach the digitalization goals of the world is new communication networks with more capabilities, including high speed, low latency, more coverage and more. 5G networks and later 6G can provide us with this infrastructure. According to 6G (KPIS) targeting, IoT equipment, and distributed systems, data volumes are beyond the tolerance of cyber systems for data analysis. On the other hand, as technology evolves, its abuse will increase, and attacks on data exploitation will become more and more diverse. The main weaknesses of distributed and IoT systems, which are their computing power and power, will remain the same, and hackers will make the most of these weaknesses and will use new methods and ways to anonymize their activities. So there is a need for a system to identify and counter potential abuses of capabilities and data volume in next generation networks, especially 5G and 6G, more than ever. In this paper, we present a theory for work and activity on the creation of malicious traffic identification modeling in 5G and 6G networks. And finally we can come up with a solution to create more security in the future.