Application Analysis and Development Recommendations for the Generative Adversarial Networks in Enhancing Automobile Data Security

The security of data generated by vehicles during operation is critically important, especially as the number of intelligent and connected vehicle users continues to rise, leading to the rapid increase of automobile communication data. In response, researchers have employed GAN s to address data security challenges within this domain, achieving significant outcomes. This paper primarily focuses on personal information identification, data desensitization, and secure transmission of data within the framework of automobile data security. The latest research on GAN s is reviewed and analyzed to assess the feasibility, strengths, and limitations for automotive data security, and the insights into future development recommendations are also provided in this domain.