TY - JOUR
AU - Kumar, Chiranjeev
AB - Vehicular Ad Hoc Networks (VANETs) are vital additives of ITS (Intelligent Transport Systems), as they drastically improve avenue safety by supplying up-to-date visitor records, such as traffic congestion and accidents the records supplied. Unscrupulous those who breach the community can manipulate visitors data, developing a risky state of affairs. Consequently, securing VANETs by enforcing strong algorithms to hit upon and prevent undesirable malicious visitors is essential. A privacy-keeping authentication approach is proposed to overcome this hassle. The approach prioritises verifying the motors earlier than connecting to the car community, detecting and disposing of malicious content material accordingly. The instance is administered on a Docker field that internally clones the network on a Linux gadget using Ubuntu 20.04. This framework affords a regulated and steady test environment to evaluate the performance of the proposed solution. Pseudo-IDs are assigned to compromised vehicles to ensure confidentiality. This technique ensures the identification of the cars even during a communications failure. The implementation results of the model display high performance, speedy verification time, and occasional computational cost compared to different methods. These homes are essential inside the vehicular community surroundings, wherein speedy and green conversation is critical to retaining traffic flowing and ensuring protection and privateness-shielding authenticated users. Its implementation’s usefulness and robustness are validated with its usage in a Docker box that mimics Linux surroundings. This technique shows a top-notch development in smart transportation systems and offers a viable technique for vehicular network protection.
TI - Secured VANET Using Privacy-Preserving Authentication Approach
JF - SN Computer Science
DO - 10.1007/s42979-025-04152-5
DA - 2025-06-30
UR - https://www.deepdyve.com/lp/springer-journals/secured-vanet-using-privacy-preserving-authentication-approach-0e8eIRluyr
VL - 6
IS - 6
DP - DeepDyve
ER -