Research on the Algorithm of Situational Element Extraction of Internet of Vehicles Security based on Optimized-FOA-PNN

The scale of the intelligent networked vehicle market is expanding rapidly, and network security issues also follow. A Situational Awareness (SA) system can detect, identify, and respond to security risks from a global perspective. In view of the discrete and weak correlation characteristics of perceptual data, this paper uses the Fly Optimization Algorithm (FOA) based on dynamic adjustment of the optimization step size to improve the convergence speed, and optimizes the extraction model of security situation element of the Internet of Vehicles (IoV), based on Probabilistic Neural Network (PNN), to improve the accuracy of element extraction. Through the comparison of experimental algorithms, it is verified that the algorithm has fast convergence speed, high precision and good stability.