Based on the characteristics and data security requirements of the cloud environment, we present a scheme for a multi-security-level cloud storage system that is combined with AES symmetric encryption and an improved identity-based proxy re-encryption (PRE) algorithm. Our optimization includes support for fine-grained control and performance optimization. Through a combination of attribute-based encryption methods, we add a fine-grained control factor to our algorithm in which each authorization operation is only valid for a single factor. By reducing the number of bilinear mappings, which are the most time-consuming processes, we achieve our aim of optimizing performance. Last but not least, we implement secure data sharing among heterogeneous cloud systems. As shown in experiment, our proposed multi-security-level cloud storage system implements services such as the direct storage of data, transparent AES encryption, PRE protection that supports fine-grained and ciphertext heterogeneous transformation, and other functions such as authentication and data management. In terms of performance, we achieve time-cost reductions of 29.8% for the entire process, 48.3% for delegation and 47.2% for decryption.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.