# A Decentralized Blockchain-Based Trust Management Framework for Vehicular Ad Hoc Networks
## 1 Introduction
### Literature Review  
The number of publications that have focused on providing trust management schemes for IoV has greatly increased in recent years [7; 8; 9]. In [10] a comprehensive review of existing trust management methods is presented. The authors present an adversary-oriented survey where they have discussed the attacks that can bypass the trust management schemes and how to mitigate them. The authors in [8] discuss trust management in vehicular environments from different perspectives. Additionally, they have classified the existing trust management schemes into two categories. The first category is the artificial intelligence-based approaches based on clustering, reinforcement learning, fuzzy logic, and game theory techniques. The second category is emerging technologies-based approaches based on Cloud, Fog, Edge, Blockchain, and Software-defined networking (SDN). These new technologies improve classic trust computing approaches in terms of accuracy, aggregation, and sharing of the trust values. Moreover, classic approaches (not based on emerging technologies) often rely on recommendation systems to enhance the accuracy and consistency of the trust metrics like in [13; 14]. In [13] the authors designed a decentralized trust management framework based on fuzzy logic-based and Q-learning approaches. Each vehicle assesses the trustworthiness of its 1-hop neighbors based on a direct and an indirect trust. The direct trust is evaluated based on the direct experience with the target vehicle, particularly, the forwarding ratio, the ratio of legitimate forwarded messages, and the percentage of the detected incidents reported by the target vehicle. The indirect trust is evaluated based on recommendations received from other vehicles about the target vehicle. [PERSON] et al. proposed in [14] a lightweight trust-aware multicast routing protocol using a feedback mechanism and Markov prediction algorithm. They combined subjective trust with recommendations to create an attack-resistant trust inference model for VANETs. In both approaches, the accuracy of the trust values depends on the number of recommendations received from other vehicles, which makes it non-suitable for rural scenarios which are usually not dense. In [15], a distributed trust computing framework named EDTCF to compute the trust metrics of the vehicles in a VANET. Each vehicle solely assesses the trust metrics of its neighbors based on the credibility of their broadcast messages. However, it does not share them with other vehicles, in so doing, each vehicle in the network will have many trust metrics at the same time. Thereby, the trust metrics of each vehicle may be non-consistent with each other. Like many classic models, EDTCP [15] suffer also from the cold start problem because the trust metrics are not shared between the vehicles mainly in distributed approaches. Blockchain is a modern technology that appeared in the last decade and it has grown quickly to provide a lot of promises. It is a distributed ledger that provides a secure and transparent way to create, verify and record any type of transaction [16]. It solves the issues related to trust in any particular type of communication. Blockchain technology comprises several technologies, such as cryptographic hash, digital signatures, and consensus algorithms. Blockchain is an emerging technology used today to improve the trust management scheme [8]. Although tremendous efforts have been made to provide trust management schemes for VANETs, the research on blockchain-based trust management schemes is still limited. In [16] a blockchain-based trust management scheme is proposed for vehicular networks. It is a decentralized and hybrid scheme where each vehicle calculates first a trust rating about the received messages, then uploads the results to the nearest RSU.