k-anonymity in Resource Allocation for Vehicle-to-Everything (V2X) Systems

Abstract

Sixth generation (6G) vehicle-to-everything (V2X) systems face numerous security threats, including Sybil and denial-of-service (DoS) cyber-attacks. To provide a secure exchange of data and protect users' identities in 6G V2X communication systems, anonymization techniques - such as k-anonymity - can be used. In this work, we study centralized vs. k-anonymity based resource allocation methods in a vehicular edge computing (VEC) network. Allocation decisions for vehicular networks are classically posed as a centralized optimization task. Therefore, an information flow is transmitted from the vehicles to the communication premises. In addition to a resource allocation decision, vehicle information is not required. We analyze the centralized allocation versus k-anonymous allocation models. To show a potential deterioration introduced by anonymity, we quantify the gap in the optimal goal in two cases: based on resource allocation and with aim at energy reduction. Our numerical results indicate that energy consumption rises by 1% in smaller scenarios and 23% in medium scenarios, whereas it decreases by 14% in larger scenarios.