On the Elliptic Curve Cryptography for Privacy-Aware Secure ACO-AODV Routing in Intent-Based Internet of Vehicles for Smart Cities

TLDR: The Elliptic Curve Cryptography (ECC) based Ant Colony Optimization Ad hoc On-demand Distance Vector (ACO-AODV) routing protocol is proposed which avoids suspicious vehicles during message dissemination in IoV.

Abstract: Internet of Vehicles (IoV) in 5G is regarded as a backbone for intelligent transportation system in smart city, where vehicles are expected to communicate with drivers, with road-side wireless infrastructure, with other vehicles, with traffic signals and different city infrastructure using vehicle-to-vehicle (V2V) and/or vehicle-to-infrastructure (V2I) communications. In IoV, the network topology changes based on drivers’ destination, intent or vehicles’ movements and road structure on which the vehicles travel. In IoV, vehicles are assumed to be equipped with computing devices to process data, storage devices to store data and communication devices to communicate with other vehicles or with roadside infrastructure (RSI). It is vital to authenticate data in IoV to make sure that legitimate data is being propagated in IoV. Thus, security stands as a vital factor in IoV. The existing literature contains some limitations for robust security in IoV such as high delay introduced by security algorithms, security without privacy, unreliable security and reduced overall communication efficiency. To address these issues, this paper proposes the Elliptic Curve Cryptography (ECC) based Ant Colony Optimization Ad hoc On-demand Distance Vector (ACO-AODV) routing protocol which avoids suspicious vehicles during message dissemination in IoV. Specifically, our proposed protocol comprises three components: i) certificate authority (CA) which maps vehicle’s publicly available info such as number plates with cryptographic keys using ECC; ii) malicious vehicle (MV) detection algorithm which works based on trust level calculated using status message interactions; and iii) secure optimal path selection in an adaptive manner based on the intent of communications using ACO-AODV that avoids malicious vehicles. Experimental results illustrate that the proposed approach provides better results than the existing approaches.