Balancing Security with Performance for Cloud Databases: Data in Transit

Cloud databases are increasingly adopted due to their flexibility, high availability, and cost-effectiveness; however, they introduce significant security challenges. Ensuring data security remains a core concern, with existing methods such as encryption and monitoring often prioritising protection without adequately addressing performance implications. Moreover, while considerable attention has been given to safeguarding data at rest, data in transit has received limited focus despite being more vulnerable to threats such as man-in-the-middle attacks and eavesdropping. This study addresses this gap by investigating the performance impact of securing data in transit within cloud database environments. An empirical study was conducted using experimental research and quantitative analysis in a simulated cloud database setting. A baseline configuration with minimal security provided a benchmark for evaluating the effects of various security mechanisms. Performance was measured using predefined metrics, including execution time, memory usage, and network latency, enabling a systematic assessment of the trade-off between security and efficiency. The results support the hypothesis that an optimal balance between robust data-in-transit security and acceptable performance can be achieved. This work contributes to the underexplored domain of cloud database, data in transit security by providing empirical evidence on performance trade-offs and offering recommendations for future research and practice.