# A Secure and Efficient Authentication Scheme for Fog-Based Vehicular Ad Hoc Networks
## 2 Related Works  
This study introduces several papers that have described fog-based VANETs. [PERSON] et al. [9] proposed a vehicular fog-computing architecture that uses vehicles as the infrastructures to improve communication and computational capacity. This architecture performs communication and computation by efficiently employing the resources of individual vehicles via a collaborative aggregation of end-user clients or nearby edge devices. Combining the resources of individual vehicles significantly improves the quality of vehicular applications and services. [PERSON] et al. [10] proposed a framework for data clustering to reduce traffic data at the edge of vehicular networks using fog computing. The proposed framework for data clustering introduces two techniques to minimize the traffic information flow: a baseline technique that detects traffic congestion and two modified clustering techniques that order points to identify the clustering structure and density-based spatial clustering of applications with noise. This framework maintains high accuracy, even in highly congested vehicular traffic conditions, and reduces the communication costs in VANETs. [PERSON] et al. [11] introduced a framework for applying fog-computing technology in a VANET environment. Furthermore, they proposed a proof-of-concept system for data analyses in a fog-based VANET environment. Their study applied actual VANET data to demonstrate that fog computing is as effective as cloud computing. Their study demonstrated that distributed fog nodes can cooperate to process crucial data, quickly providing reliable data for smart city decision support systems. [PERSON] et al. [12] designed a priority-based fog-computing model for smart-city vehicle transportation to reduce delays and latency. When the fog node was overloaded, they redirected high-priority requests to an adjacent node and transmitted low-priority requests to the cloud for additional processing. This technique reduced latency and delays by 20% and 35%, respectively, compared to the cloud computing architecture, allowing efficient communication between devices. This research introduces several papers describing authentication protocols in wireless communication environments. For example, in 2017, [PERSON] et al. [13] proposed a triparty authenticated key agreement (AKA) protocol using a fog-computing facility in a healthcare environment. The proposed protocol uses bilinear pairing cryptography and decoy technology to access and store private healthcare data securely. In 2018, [PERSON] et al. [14] proposed a triparty AKA protocol for fog-based healthcare systems. They employed an elliptic curve cryptosystem and bilinear pairing to guarantee the security of the session key. In 2018, [PERSON] et al. [15] described a secure data aggregation protocol for smart grids using fog computing based on the additive privacy scheme proposed by [PERSON]. Moreover, in 2018, [PERSON] et al. [16] introduced an efficient and privacy-preserving aggregation scheme using fog-computing architecture to maintain aggregator anonymity. This protocol uses differential privacy and homomorphic encryption to safeguard aggregator obliviousness. In [13,14], computationally expensive cryptographic technology was used for the authentication phase. Bilinear pairing cryptography has high communication costs due to its computational complexity and the additional data required for key generation and data transmission. Moreover, precise data, such as healthcare information, demand high accuracy and reliability, increasing the latency. However, in fog-based VANETs, low latency is vital due to the importance of real-time data transmission and quick decision-making between vehicles. Therefore, the methods in [13,14] are inefficient and unsuitable for fog-based VANETs. In [15,16], the smart-grid environment is based on static data and designed without considering the dynamic network scalability, resulting in a lack of real-time data processing and responsiveness to dynamic situations.