Keyword-Based Medical Cloud Storage Integrity Auditing with Privacy Protection and Data Dynamics

Abstract

Keyword-based remote integrity auditing schemes effectively address the integrity of electronic medical records (EMRs) stored in the cloud. In practice, users expect to be able to perform flexible dynamic data updates while also protecting data privacy against a third-party auditor during the auditing process. However, existing schemes fail to simultaneously satisfy both requirements: they either incur prohibitive overhead for block-level updates or disclose to the auditor which EMRs match the target keyword and the number of such EMRs. To address this, we propose a new keyword-based auditing scheme for medical cloud. Specifically, we design a novel authentication identifier set. Unlike the keyword tags in Shen et al.’s scheme, this set aggregates the block hashes and thereby enables the auditor to verify integrity without obtaining sensitive information. Furthermore, we introduce a dynamic hash list. By updating this list during block insertion and deletion, the scheme eliminates the need to recompute the authenticators of subsequent blocks, significantly enhancing the efficiency of dynamic data updates. Security analysis confirms that the proposed scheme is secure. Performance analysis shows our scheme reduces block insertion and deletion overhead by over 60% compared to Gao et al.’s scheme, demonstrating high efficiency and practicality.