Research on the Construction of Cybersecurity Governance Model and Multiple Regression Analysis of Data Security in Airline Division

Abstract

Abstract The aviation industry is witnessing an increasing adoption of new technologies in the automation process, which improves efficiency and enhances the customer experience while invariably creating vulnerabilities and threatening data security. This paper takes Air Macau as an example and proposes an RQP algorithm to quantify the likelihood of risk occurrence in the cross-border flow of important aviation data in Air Macau and the degree of impact after the risk occurrence. According to the descriptive statistical analysis of the regression variables, the overall risk mean value of the data transmission node is 8456.154. The aviation industry significantly positively influences the risk of cross-border data flow compared to the company, with a regression coefficient of 0.487 and a P value less than 0.05. Combining Paillier and RSA algorithms, we construct the data analysis and authentication model for cybersecurity governance and implement encrypted cross-border transmission of aviation data. We design simulation experiments to assess the model’s performance and security. The encryption time and decryption time of this scheme, for a length of 256 bytes, are 0.201 ms and 0.135 ms, respectively, making it more efficient than other algorithms. This ensures the security of encrypted data transmission by the airline company and holds significant importance for the cross-border data flow in Air Macau.