Abstract—Self-driving vehicles face critical security and privacy threats, including the misuse of real-time vehicle location data, GPS spoofing, and unauthorized access. This work aims to develop a privacy-preserving authentication protocol that verifies geofence compliance without revealing exact coordinates and enables user-controlled response to anomalies. The proposed method integrates 5G communication, Elliptic Curve Cryptography, and Zero- Knowledge Proofs, with biometric-based multi-factor authentication for breach handling. Formal verification using ProVerif was employed to analyze secrecy of the vehicle location and to verify authentication correspondences between the vehicle, cloud, and user. While MATLAB simulations under realistic 5G parameters demonstrate low latency (23.34 ms), minimal communication overhead (7.5 KB), and high detection rates (90%) in 10-vehicle scenarios. These findings highlight the protocol’s potential to provide secure, scalable, and privacy-preserving solutions for selfdriving vehicle networks. This work provides a foundational framework for future advancements in the security of autonomous systems and privacy-preserving technologies.