Preventing Cross Network Slice Disruptions in a Zero-Trust and Multi-Tenant Future 5G Networks

As network slicing is the chief enabler for future Beyond 5G(B5G) and 6G networks, multiple tenants interoperate cost-effectively to provide a variety of slice services on a common physical infrastructure. However, this opens the doors to cross-slice disruptions with Man-in-the-Middle (MITM) attack which ultimately disrupts the slice services in the data plane. In this paper, we address such possible cross-network slice disruptions in a zero-trust and multi-tenant based 5G network by proposing different design techniques namely, secure communication and Artificial Intelligence (AI)-based anomaly detection to prevent them. Our experiments on a 5G testbed prototype show that in the secure communication method, Attribute-Based Encryption (ABE) provides higher security benefits in confidentiality and implicit authorization. However, symmetric encryption and integrity protection prevent cross-slice disruptions with less communication overhead, but with a weaker security level. On the other hand, with online learning and noise tolerance capabilities, AI-based Hierarchical Temporal Memory (HTM) can proactively detect the occurrences of the identified cross-slice disruptions.