Privacy-Preserving Analysis Framework of Flight Test Data Based on Hybrid Cloud Architecture

With the rapid development of aviation equipment, advanced airborne systems are more complicated than before. Therefore, the types and quantities of flight test parameters have also increased significantly. Obviously, the engineering data formed and generated during the flight test have characteristics big data. Considering the requirements of flight test for completeness, accuracy and timeliness of data processing, traditional data storage and processing methods are difficult to process large-scale flight test engineering data, which is not conducive to the application of test data mining. Cloud computing can provide powerful computing power and storage capacity. Compared with traditional computing, cloud computing has great advantages in computing power, scalability and user cost. However, the problems of data security and privacy leakage caused by it cannot be ignored. Based on the advantages and disadvantages of cloud computing, this paper focuses on the storage and processing of flight test data, aiming at designing a secure and efficient data analysis framework, which can give play to the boosting role of flight test engineering big data.