Modern vehicles are no longer simply mechanical devices. Connectivity between the vehicular network and the outside world has widened the security holes that hackers can use to exploit a vehicular network. Controller Area Network (CAN), FlexRay, and automotive Ethernet are popular protocols for in-vehicle networks (IVNs) and will stay in the industry for many more years. However, these protocols were not designed with security in mind. They have several vulnerabilities, such as lack of message authentication, lack of message encryption, and an ID-based arbitration mechanism for contention resolution. Adversaries can use these vulnerabilities to launch sophisticated attacks that may lead to loss of life and damage to property. Thus, the security of the vehicles should be handled carefully. In this paper, we investigate the security vulnerabilities with in-vehicle network protocols such as CAN, automotive Ethernet, and FlexRay. A comprehensive survey on security attacks launched against in-vehicle networks is presented along with countermeasures adopted by various researchers. Various algorithms have been proposed in the past for intrusion detection in IVNs. However, those approaches have several limitations that need special attention from the research community. Blockchain is a good approach to solving the existing security issues in IVNs, and we suggest a way to improve IVN security based on a hybrid blockchain.

An increasing number of vehicles on the roads increases the risk of accidents. In bad weather (e.g., heavy rainfall, strong winds, storms, and fog), this risk almost doubles due to bad visibility as well as road conditions. If an accident happens, especially in bad weather, it is important to inform approaching vehicles about it. Otherwise, there might be another accident, i.e., a multiple-vehicle collision (MVC). If the Emergency Operations Center (EOC) is not informed in a timely fashion about the incident, fatalities might increase because they do not receive immediate first aid. Detecting humans or animals would undoubtedly provide us with a better answer for reducing human fatalities in traffic accidents. In this research, an accident alert light and sound (AALS) system is proposed for auto accident detection and alerts with all types of vehicles. No changes are required in non-equipped vehicles (nEVs) and EVs because the system is installed on the roadside. The idea behind this research is to make smart roads (SRs) instead of equipping each vehicle with a separate system. Wireless communication is needed only when an accident is detected. This study is based on different sensors that are used to build SRs to detect accidents. Pre-saved locations are used to reduce the time needed to find the accident’s location without the help of a global positioning system (GPS). Additionally, the proposed framework for the AALS also reduces the risk of MVCs.

In this paper, we propose a Proof-of-Location (PoL)-based location verification scheme for mitigating Sybil attacks in vehicular ad hoc networks (VANETs). For this purpose, we employ smart contracts for storing the location information of the vehicles. This smart contract is maintained by Road Side Units (RSUs) and acts as a ground truth for verifying the position information of the neighboring vehicles. To avoid the storage of fake location information inside the smart contract, vehicles need to solve unique computational puzzles generated by the neighboring RSUs in a limited time frame whenever they need to report their location information. Assuming a vehicle has a single Central Processing Unit (CPU) and parallel processing is not allowed, it can solve a single computational puzzle in a given time period. With this approach, the vehicles with multiple fake identities are prevented from solving multiple puzzles at a time. In this way, we can mitigate a Sybil attack and avoid the storage of fake location information in a smart contract table. Furthermore, the RSUs maintain a dedicated blockchain for storing the location information of neighboring vehicles. They take part in mining for the purpose of storing the smart contract table in the blockchain. This scheme guarantees the privacy of the vehicles, which is achieved with the help of a PoL privacy preservation mechanism. The verifier can verify the locations of the vehicles without revealing their privacy. Experimental results show that the proposed mechanism is effective in mitigating Sybil attacks in VANET. According to the experiment results, our proposed scheme provides a lower fake location registration probability, i.e., lower than 10%, compared to other existing approaches.