Big data security: Requirements, challenges and preservation of private data inside mobile operators

Abstract

Today's mobile operators (MOs) are experiencing tremendous amount of data usage of their subscribers. This results in data tsunami arriving from various sources inside MOs' network infrastructures. On the other hand, handling this data increase in an elegant manner will be utmost importance for designing the next generation cellular 5G network infrastructure. In this evolving 5G architecture, there will also be many vertical market players from different domains (e.g. car manufacturers, retailers, banks, transportation providers) as well as third party players (e.g. application developers) that will be interacting with MO's subscribers private data through many innovative big data applications. These big data applications can provide additional value added services to MOs. On the other hand, ensuring the security of these applications utilizing big data will be another dimension that needs to be provisioned carefully. In this paper, we study the various security requirements and challenges of running big data application services by MOs themselves. Based on the system architecture that is studied, we have also run extensive vulnerability tests against one example of big data application deployed inside MO's premises. Our results indicate key security findings and map some of the missing requirements into the considered big data application scenario.