Malicious Route Detection in Vehicular Ad-hoc Network using Geographic Routing with Masked Data

Background: Vehicular Ad-hoc Network is the subset of Mobile Ad-hoc Network, Intelligent Transport System and Internet of Things. The acting nodes in VANET are the vehicles on the road at any moment. Objective: The anonymity character of these vehicles is opening the opportunity for malicious attacks. Malicious routes increase the data retransmission and hence, the performance of routing will be degraded. The main objective this work is to identify the malicious routes, avoid the data transmission using these routes and increase the packet delivery ratio. Methods: In the proposed system called Geographic Routing Protocol with Masked data, two binary- codes called mask and share have been generated to identify the malicious route. The original data is encoded using these binary-codes and routed to the destination using the geographic routing protocol. It is reconstructed at the destination node and based on the encoding technique the malicious routes and malicious nodes are identified. Simulations were conducted with varying speed and varying network size in 20 km2 geographical area. Results: The average packet delivery ratio with varying speed is 0.817 and with varying networksize is 0.733. Conclusion: The proposed geographical routing protocol with masked data technique outperforms than traditional geographic protocol and Detection of Malicious Node protocol, by 0.102 and 0.264 respectively with different speeds and by 0.065 and 0.1616 respectively with different network size.