Secure and Flexible Data Management of UAVs Based on Searchable Symmetric Encryption

Unmanned Aerial Vehicles (UAVs) are extensively employed to monitor varied tasks, leading to substantial sensitive aerial data. With the limited resources of UAVs, task data is typically encrypted and uploaded to cloud platforms for secure storage and analysis. However, outsourcing data introduces significant security challenges in search, update, and data management. To solve those challenges, we propose a secure and flexible data management framework named Attribute-oriented Mergeable Searchable Symmetric Encryption(AoMS \(^2\) E) where attributes are metadata such as flight area or task identifier as attributes in agricultural UAV ecosystems. By integrating a novel \(\omega \) -tree index structure and tailored cryptography tools, the AoMS \(^2\) E supports retrieval, updates, and dynamic merging over encrypted data. The rigorous security proof and comprehensive experiments show the security and efficiency of AoMS \(^2\) E.