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.

Vertical industries start taking advantage of computing continuum by hosting their applications or using additional services offered by several Cloud Service Providers. Computing continuum has many advantages for Verticals as it allows to fulfil their quality of service requirements and save costs. This could be achieved due to the distributed, heterogenous and dynamic nature of infrastructure of computing continuum and Vertical’s application mobility thus its ability to migrate between different environments. However, this can progress only if in parallel to Vertical’s application mobility, the security requirements are dynamically managed and met at the required level in each environment. It is particularly important due to new regulations (e.g. Cyber Resilience Act and Network and Information Security Directive - NIS2) which define new critical industries and introduce for them additional security obligations. Noncompliance with these regulations could lead to penalties. Therefore, Verticals will have to fulfil specific security requirements and be able to deliver proof of compliance. In this paper, we propose to address those needs using emerging concept of Security Service Level Agreement. Following that, we propose a novel Security Service Level Agreement Mediator for cloud applications in mobility which negotiates Security Service Level Agreement with Verticals, continuously fulfils it in computing continuum and delivers proofs of compliance. Based on that, we define main challenges for setting up the Security Service Level Agreement Mediator on the basis of considerations presented in this paper.

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.

Transitioning edge and cloud computing in 5G networks towards service-based architecture increases their complexity as they become even more dynamic and intertwine more actors or delegation levels. In this paper, we demonstrate the Liability-aware security manager Analysis Service (LAS), a framework that uses machine learning techniques to compute liability and trust indicators for service-based architectures such as cloud microservices. Based on the commitments of Service Providers (SPs) and real-time observations collected by a Root Cause Analysis (RCA) tool GRALAF, the LAS computes three categories of liability and trust indicators, specifically, a Commitment Trust Score, Financial Exposure, and Commitment Trends.

In this article we setup a dynamic device-to-device communication system where devices, given as a Poisson point process, move in an environment, given by a street system of random planar-tessellation type, via a random-waypoint model. Every device independently picks a target location on the street system using a general waypoint kernel, and travels to the target along the shortest path on the streets with an individual velocity. Then, any pair of devices becomes connected whenever they are on the same street in sufficiently close proximity, for a sufficiently long time. In our main results we isolate regimes for the almost-sure absence of percolation if, for example, the device intensity is too small, or the connectivity time is too large. On the other hand, we exhibit parameter regimes of sufficiently large intensities of devices, under favorable choices of the other parameters, such that percolation is possible with positive probability. Most interestingly, we also show an in-and-out of percolation as the velocity increases. The rigorous analysis of the system mainly rests on comparison arguments with simplified models via spatial coarse graining and thinning approaches. Here we also make contact to geostatistical percolation models with infinite-range dependencies.