Genetic and Decision Tree-Based Secure Data Dissemination Framework for Autonomous Vehicles

In this article, we proposed a hybrid model comprising a genetic algorithm and a decision tree for secure data exchange in autonomous vehicles (AVs). The integration of a genetic algorithm enables systematic feature optimization, enhancing the accuracy and efficiency of classification models. Extensive performance assessments, including metrics such as receiver operating characteristic (ROC) curve and a convergence curve, substantiate the effectiveness of the proposed framework in addressing classification tasks. A robust model is presented that could thrive in the dynamic environment of AV, as a result of which the security and efficiency of the Intelligent Transportation Systems is further strengthened. We focus on the practical implications of our research, and consequently, the real-world applications relating to the evolving AV environment.