Vehicular ad hoc networks (VANETs) have become increasingly common in recent years due to their critical role in the field of smart transportation by supporting Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. The security and privacy of VANET are of the utmost importance due to the use of an open wireless communication medium where messages are exchanged in plain text, something which allows attackers to intercept, tamper, replay, and delete them. Hence, there is a high probability that the safety of a VANET-based smart transportation system could be compromised. Nowadays, securing and safeguarding the exchange of messages in VANETs is the focus of many security research teams, as reflected by the number of authentication and privacy schemes that have been proposed. However, these schemes have not fulfilled all aspects of the security and privacy requirements. The present paper is an effort to provide a thorough background on VANETs and their components; various types of attacks on them; and all the security and privacy requirements for authentication and privacy schemes for VANETs. This paper is among the first to provide a comprehensive survey of the existing authentication and privacy schemes and compare them based on all security and privacy requirements, computational and communicational overheads, and the level of resistance to different types of attacks. It also provides a qualitative comparison with the existing surveys. This paper could serve as a guide and reference in the design and development of any new security and privacy techniques for VANETs.

The security of the internet is seriously threatened by a distributed denial of service (DDoS) attacks. The purpose of a DDoS assault is to disrupt service and prevent legitimate users from using it by flooding the central server with a large number of messages or requests that will cause it to reach its capacity and shut down. Because it is carried out by numerous bots that are managed (infected) by a single botmaster using a fake IP address, this assault is dangerous because it does not involve a lot of work or special tools. For the purpose of identifying and analyzing DDoS attacks, this paper will discuss various machine learning (ML) and deep learning (DL) techniques. Additionally, this study analyses and comparatives the significant distinctions between ML and DL techniques to aid in determining when one of these techniques should be used.

Fifth-generation (5G)-enabled vehicular fog computing technologies have always been at the forefront of innovation because they support smart transport like the sharing of traffic data and cooperative processing in the urban fabric. Nevertheless, the most important factors limiting progress are concerns over message protection and safety. To cope with these challenges, several scholars have proposed certificateless authentication schemes with pseudonyms and traceability. These schemes avoid complicated management of certificate and escrow of key in the public key infrastructure-based approaches in the identity-based approaches, respectively. Nevertheless, problems such as high communication costs, security holes, and computational complexity still exist. Therefore, this paper proposes an efficient certificateless authentication called the ECA-VFog scheme for fog computing with 5G-assisted vehicular systems. The proposed ECA-VFog scheme applied efficient operations based on elliptic curve cryptography that is supported by a fog server through a 5G-base station. This work conducts a safety analysis of the security designs to analysis the viability and value of the proposed ECA-VFog scheme. In the performance ovulation section, the computation costs for signing and verification process are 2.3539 ms and 1.5752 ms, respectively. While, the communication costs and energy consumption overhead of the ECA-VFog are 124 bytes and 25.610432 mJ, respectively. Moreover, comparing the ECA-VFog scheme to other existing schemes, the performance estimation reveals that it is more cost-effective with regard to computation cost, communication cost, and energy consumption.

Over the past years, vehicular ad hoc networks (VANETs) have been commonly used in intelligent traffic systems. VANET’s design encompasses critical features that include autonomy, distributed networking, and rapidly changing topology. The characteristics of VANET and its implementations for road safety have attracted considerable industry and academia interest, particularly in research involving transport systems enhancement that could potentially save lives. Message broadcasting in an open access system, such as VANET, is the main and utmost challenging problem with regard to security and privacy in VANETs. Various studies on VANET security and privacy have been proposed. Nevertheless, none has considered overall privacy requirements such as unobservability. In order to address these shortcomings, we propose a VANET based privacy-preserving communication scheme (VPPCS), which meets the requirements for content and contextual privacy. It leverages elliptic curve cryptography (ECC) and an identity-based encryption scheme.We have carried out a detailed security analysis (burrows–abadi–needham (BAN) logic, random oracle model, security of proof, and security attributes) to validate and verify the proposed scheme. The analysis has shown that our scheme is secure and also shown to be effective in a performance evaluation. The proposed scheme does not only meet the previously mentioned security and privacy requirements, but also impervious to various types of attacks such as replay, impersonation, modification, and man-in-themiddle attacks.

Innovative framework on Vehicles in Network Simulation (VEINS) for Vehicular Ad-hoc Network (VANET) that use security aspect is mainly limited and dispersed. In order to offer valuable visions for technical settings and researchers, the study looked into the trends and gaps that were currently present. As a result, this systematic literature review was carried out to develop a comprehensive taxonomy of the research landscape. A thorough study was done for papers about (a) VANET, (b) VEINS, and (C) security aspects. This research used three databases, namely IEEE Xplore, ScienceDirect, and Scopus. These databases included in-depth research focused on VANET based on the VEINS framework. Then, on the basis of the security aspect, filtering was accomplished. The first class includes threats and vulnerabilities that evaluate the effects of threats and vulnerabilities on VANETs by using the VEINS framework and suggest ways to mitigate or lessen their effects. The second category includes articles on the solution technology that uses blockchain, machine learning, and Software-Defined Networking (SDN) techniques in VEINS-based VANET applications. The third class comprises the requirements that satisfy privacy, authentication, trust management, reliability, and revocation of the VANET security-based VEINS framework. Finally, this paper reviews the architecture and bidirectional coupling of the VEINS framework.

The fifth-generation (5G) technology-enabled vehicular network has been widely used in intelligent transportation in recent years. Since messages shared among vehicles are always broadcasted by openness environment’ nature, which is vulnerable to several privacy and security problems. To cope with this issue, several researchers have proposed pseudonym authentication schemes for the 5G-enabled vehicular network. Nevertheless, these schemes applied complected and time-consumed operations. Therefore, this paper proposes a fog computing-based pseudonym authentication (FC-PA) scheme to decrease the overhead of performance in 5G-enabled vehicular networks. The FC-PA scheme applies only one scalar multiplication operation of elliptic curve cryptography to prove information. A security analysis of our work explains that our scheme satisfies privacy-preserving and pseudonym authentication, which are resilient against common security attacks. With performance efficiency, our work can obtain better trade-offs between efficiency and security than the well-known recent works.