Secure and Fast Query Approach for High-Precision Multi-dimensional Satellite Remote Sensing Data

High-precision satellite remote sensing data provides rich and accurate Earth observation information that can be used for various remote sensing applications. In this era of edge computing with the Internet of Things at its core, network edge devices generate massive amounts of real-time data. However, network edge data, such as remote sensing data, may contain sensitive information. Therefore, ensuring the security of massive remote sensing data while providing fast and secure retrieval has become a challenge. However, many existing solutions only address problems in single-dimensional remote sensing data scenarios, while others are not efficient. Therefore, we propose a secure and fast query approach for high-precision multi-dimensional satellite remote sensing data (SFQA) to address the efficiency and security issues of querying multi-dimensional remote sensing data. In SFQA, we use more efficient encoding techniques to replace the complex and time-consuming encryption algorithms used in traditional methods. Additionally, we construct a secure index to achieve secure and efficient querying of massive high-resolution multi-dimensional satellite remote sensing data. Experimental results and analysis show that the SFQA method performs efficiently in querying high-resolution multi-dimensional satellite remote sensing data. Furthermore, our security analysis confirms that no external entity can access or obtain any additional information throughout the entire query process, ensuring the confidentiality and privacy of remote sensing data.