Enhancing Data Security in Internet of Vehicular Things (IoVT) through Blockchain-based Solutions
Satvik Vats, Shiva Mehta, Choudhary Ravi Singh · 2024
In the current situation, it has been confirmed that VANET, which is used to communicate between vehicles, has more capacity than MANET, which refers to conventional mobile ad-hoc networking. Therefore, the ongoing development of VANETs is the fundament for enhancing the performance of traffic management systems, reducing crashes, upgrading road safety, and wisely handling emergency cases. Modern cars are composed of various new instruments that gather millions of information about features, fuel needs, and, eventually, destinations and have become the core of the global car-sharing application. Through these wide storage units, sudden changes in plans by travelers and the need to go online for immediate preparations to travel are helped, which is the basic principle of ambient intelligence stipulated under the Internet of Things (IoT) architecture. When there is an emergency, time is crucial. For this reason, the first important step to identifying the nearest emergency facility is to conduct a rapid examination of vehicle reports. By implementing the machine learning approach that places a high focus on the anonymity of users, this paper introduces a new method of predicting vehicles’ positions based on enormous data sets. Finally, the experiment has been proven to be the most effective technique for exact vehicle position forecasting and data protection. The results clearly showed that the modeling accuracy was immensely enhanced by the prediction, which introduced a marked $12.2 \%$ improvement when compared with the previous models. Consequently, the data was calculated within $40 \%$ less time by applying the federated learning method and edge computing. Furthermore, blockchain ensures data protection and integrity, reducing the number of security vulnerabilities and attacks cases to less than $\mathbf{2 0 \%,}$ making the system safer against future cyber attacks.