5G is the fifth-generation cellular network satisfying the requirements IMT-2020 (International Mobile Telecommunications-2020) of the International Telecommunication Union. Mobile network operators started using it worldwide in 2019. Generally, 5G achieves exceptionally high values of performance parameters of access and transmission. The application of edge servers has been proposed to facilitate implementing such requirements of 5G, resulting in 5G MEC (Multi-access Edge Computing) technology. Moreover, to optimize services for specific business applications, the concept of 5G vertical industries has been proposed. In this article, we study how the application of the MEC technology affects the functioning of 5G MEC-based services. We consider twelve representative vertical industries of 5G MEC by presenting their essential characteristics, threats, vulnerabilities, and known attacks. Furthermore, we analyze their functional properties, give efficiency patterns and identify the effect of applying the MEC technology in 5G on the resultant network's quality parameters to determine the expected security requirements. As a result of the research, we identify the impact of classified threats on the 5G empowered vertical industries and identify the most sensitive cases to focus on their protection against network attacks in the first place.

MEC technology provides a distributed computing environment in 5G mobile networks for application and service hosting. It allows customers with different requirements and professional competencies to use the services offered by external suppliers. We consider a service access control framework on 5G MEC networks that is efficient, flexible, and user-friendly. Its central element is the MEC Enabler, which handles AAA requests for stakeholders accessing services hosted on the edge servers. The JSON Web Token (JWT) open standard is a suitable tool for the MEC Enabler to manage access control credentials and transfer them securely between parties. In this paper, in the context of access control, we propose the token reference pattern called JSON MEC Access Token (JMAT) and analyze the effectiveness of its available protection methods in compliance with the standard requirements of MEC-hosted services in 5G networks.

Modern and future services require ultra-reliable mobile connections with high bandwidth parameters and proper security protection. It is possible to ensure such conditions by provisioning services in the Multi-Access Edge Computing system integrated with fifth-generation mobile networks. However, the main challenge in the mentioned architecture is providing a secure service migration with all related data and security requirements to another edge computing host area when the user changes its physical location. This article aims to present the state of research on the migration of the security context between service instances in Edge/MEC servers, specify steps of the migration procedure, and identify new security challenges inspired by use cases of 5G vertical industries. For this purpose, the analysis of the security context’s structure and basic concept of the Security Service Level Agreement was performed and presented in the document. Next, a further investigation of the security context was conducted, including requirements for its reliable migration between edge serves instances. The study mainly focused on crucial migration challenges and possible solutions to resolve them. Finally, the authors presented how the proposed solution can be used to protect 5G vertical industries services based on several mobile use cases.

Multi-access Edge Computing (MEC) is one of the key enablers in 6G. By offering computing capabilities near the end users, it enables lower environmental impact, higher end-to-end latency, higher resiliency, among others. It is also a critical part in the Cloud-Edge-IoT continuum. However, the deployment of services in the edge poses some security challenges. This work aims at solving orchestration issues, such as how to deal with service deployment while meeting service-specific requirements, while at the same time meeting isolation requirements, in a multi-cluster environment. Our algorithm is estimated to be around 20% better than the baseline, while at the same time offering guarantees on the communication latency and isolation requirements, which the baseline cannot offer. We were able to build an orchestration engine, with an advanced algorithm to compute optimal placement of microservices, integrated in a state-of-art emulation platform, with industry best practice. This demonstrates the feasibility in practice and efficiency of our approach.