A Systematic Literature Review on securing Beyond 5G Network Slicing through Machine Learning and Blockchain

Research on beyond 5G (B5G) network slicing, which encompasses development of mobile networks in future, is in progress in many parts of the world. However, many challenges exist in B5G, namely, mobile device resource constraints, multilayered wireless resource management, multiple heterogeneous network architecture, increased Compute and storage demands, and increased privacy and security demands. To address these challenges, the close coupling of machine learning (ML) and blockchain suggest gains in security, privacy, efficiency and cost savings of 5G network slicing. In this paper, we conduct a thorough current surveys research done on blockchain and ML applied to 5G network slicing. A brief overview of ML and blockchain will begin the paper, followed by discussing recent research advances related both and identifying the trend of employing both.Further, we are thoroughly investigating how the combination of blockchain and ML fits with 5G network slicing with a emphasis on the applications of security services. This entails discussions on central services such as resource allocation, security and privacy. We greatly benefit existing literature, and would like to present a thorough study of ML as well as blockchain in the domain of 5G and its future directions, whilst presenting perspectives that can assist in a roadmap for future research.