Survey: Trust Management in VANET

Abstract

The Vehicular ad-hoc networks (VANET) are a subclass of MANET with vehicles as mobile nodes. The vehicles exchange data via vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communication. The securities of data communications focus on deciding data trust. The concept of trust estimates the reliability of communications data. In particular, we have mainly focused on problems of mistrust or data trust in the VANET network. In this paper, we will study some models of trust and compare them, which will help to reduce the impact of trust problem and try to improve it. *Corresponding Author: Dr. Rachid Chelouah, University of ParisSeine, ETIS laboratory, CNRS UMR8051, France; E-mail: rc@eisti.eu Citation: Bousmaha N, Maachaoui M, Chelouah R (2020) Survey: Trust Management in VANET. Int J Comput Softw Eng 5: 152. doi: https://doi. org/10.15344/2456-4451/2020/152 Copyright: © 2020 Bousmaha et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Entity-oriented trust model In this approach, we describe the models that are based on the reliability of the entity (vehicle), which is based on obtaining information about the sender and neighbor receivers. However, the change of vehicle position allows frequent interruptions, which makes difficult to have sufficient information about the neighbors. The authors of [8] propose a VANET Dynamic Demilitarized Zone (VDDZ) trust model that uses a public key infrastructure and distributed cluster algorithm. As shown in Figure 5. The objectives of the trust model VDDZ is to exclude the entry of malicious or obscure vehicles in cluster, it prohibits using directly the communication of a cluster head (CH) with other member vehicles. This technique represents a set of registration authority (RA) vehicles located 1-hop away from the certification authority. This cluster algorithm uses two parameters: 1. The trust metric (Tm): allows calculating confidence it for each vehicle. 2. The mobility metrics: preserves security and stability of cluster head. The Head cluster determines the trust level of vehicles in the cluster by a trust metric. The (Tm) is a continuous value between 0 and 1. Of course, new vehicles start with Tm = 0.1 and all vehicles with Tm <1 must behave well to increase their trust metric. Trusted vehicles are those with Tm = 1 [9], and this algorithm uses two types of messages: 1. The HELLO message, consisting of speed, identity, position, current status, Tm table and current neighbors. 2. BEACON ELECTION, consisting of an IP address, number of hops, relative mobility (RM) and number of trusted neighbors (NTN). Figure 1 describes a VDDZ. International Journal of Computer & Software Engineering Nourelimane Bousmaha1, Mohamed Maachaoui2 and Rachid Chelouah1,* University of ParisSeine, ETIS laboratory, CNRS UMR8051, France University of ParisSeine, Quartz laboratory, EA 7393, France Int J Comput Softw Eng IJCSE, an open access journal ISSN: 2456-4451 Volume 5. 2020. 152 Bousmaha et al,. Int J Comput Softw Eng 2020, 5: 152 https://doi.org/10.15344/2456-4451/2020/152