The integration of cyber-physical systems (CPS) and Internet of vehicles (IoV) improves the solution for safe driving, traffic reduction, assisted navigation, and secure communication, etc. Based on the communication and service demands, the security and privacy requirements of the users vary. Therefore, unanimous and conventional key-different security methods are required for privacy throughout the driving distance. For strengthening uninterrupted services with precise privacy, this article introduces a diversified context-based privacy-preserving scheme (DCP2S). This scheme considers two contexts, namely navigation support and information communication exchange for balancing two distinct privacy administrations. In the navigation-dependent process, privacy is ensured using two-way authentication, which is verified by the CPS, whereas a one-way authentication is sufficient for information exchange. Both authentication processes are monitored using external CPS with interchangeable security functions for securing consumer-centric communications. This means the security amendments are valid for authentication and privacy preservation regardless of service utilization. The concurrency in employing the security modes is verified using knowledge learning for preventing interrupts. More specifically, knowledge learning accumulates interruptions and failures from the previous information exchange for each of its modes. Based on this information, further authentication from the vehicle is generated; the CPS is responsible for monitoring and information sharing for joint adversary injections. The proposed scheme maximizes service utilization, interrupt detection, and authentication verification by 11.26%, 14.37%, and 7.56% respectively. Also, scheme has achieved lower service failure and authentication time by 8.98% and 445.382 ms, respectively, which is superior to existing techniques.