Improving Attack Detection in IoV Systems using GA-based Hyperparameter Optimization

The technology that enables the devices in our daily lives to communicate with each other over the internet and share data is Internet of Things (IoT). It is very important that devices and systems work efficiently in IoT applications. Internet of Vehicles (IoV) is an IoT application and an important area for traffic management, road safety and driving comfort. In this paper, an intrusion detection system based on Genetic Algorithm (GA) and Machine Learning (ML) is proposed to ensure IoV security. The efficiency of ML algorithms’ prediction has been tuned and adjusted using GA. The obtained results showed that random forest was the most successful results with 99.64% of detection accuracy. In future research, it is aimed to develop effective ML models for different IoT applications.