Data Usage Control for Privacy-Enhanced Network Analytics in Private 5G Networks
Hammad Zafar, Umberto Fattore, Flavio Cirillo, Carlos J. Bernardos · IEEE Open Journal of the Communications Society · 2024
With the rise of 5G networks and the ongoing evolution toward 6G, the proliferation of private networks has accelerated. While standalone deployments are possible, more efficient private network deployments often involve sharing parts of the private network with public operator’s infrastructure, through approaches such as public network integration, hybrid private networks, and network slicing. However, these configurations introduce privacy concerns, particularly regarding the privacy and ownership of private network data that may need to be collected by the public network operator for analytics and joint optimization across private and public networks. This paper explores data usage control mechanisms to safeguard private network data when performing management data analytics. Specifically, we propose a framework for privacy-enhanced data analytics (PEDA) consisting of components that can complement the standard 5G analytics framework. Additionally, we provide a blueprint for privacy-enhanced orchestration of analytics services across public and private 5G networks utilizing NFV-MANO as the orchestration framework. To this end, we demonstrate orchestration of analytics services across distributed infrastructures belonging to private and public 5G networks, according to the data usage policies set by data owners.