Automate Allocation of Secure Slice in Future Mobile Networks using Machine Learning
Muddu Krishnama Naidu Immadisetti, A. P. Murukessan, M. Srinivas · 2021
Flexibility is one of the primary aims of 5G Networks to support various use-case applications in mobile networks. In this work we have given the concept of fine-grain network slices which means giving a slice for network traffic of specific application. The fine-grain network slices make network more flexible to analyze, update and detect application failures. In this work we proposed a 2-tier approach for allocating a secure slice using Random Forest method. The datasets used in this work are application traffic dataset which has 50 plus different application labels like google, youtube, facebook etc and DDoS attack dataset. Random Forest model is showing promising results to allocate the secure slice for the network traffic.