DVNAT: a Dedicated Vehicular Network ArchiTecture against inconsistency and bad-mouthing attacks through a reputation system

Abstract

The VANETs (Vehicular Ad hoc Network) brought more safety and comfort to traffic, allowing the exchange of traffic messages and entertainment content between vehicles. However, several types of attacks are known on vehicle networks, causing significant problems for drivers. Inconsistency and collusion attacks by bad-mouthing, for example, can disturb the correct functioning of the network. This paper presents DVNAT (Dedicated Vehicular Network ArchiTecture), which is capable of handling these types of attacks on vehicular networks. It uses a digital signature with the Ed25519 algorithm and a centralized reputation system with the LETICIA (Lightweight and EfficienT Information exChange In Ad-hoc network) algorithm developed to mitigate malicious vehicle attacks on the network. Simulation results show that DVNAT with the LETICIA algorithm effectively reduced the reputation of the malicious vehicle against inconsistency attacks while maintaining the reputation of the vehicle honest against bad-mouthing collusion attacks when compared to the ARS algorithms, BYOR, BYOR-LF, and IDES algorithms.