A privacy-preserving public integrity check scheme for outsourced EHRs

Cloud storage as an emerging technology has already drawn people's attention and hospitals and medical institutions increasingly begin to outsource their huge electronic health records (EHRs) to cloud. Since EHRs always involve lots of sensitive privacy, it is necessary to protect the confidentiality and privacy of EHRs. Meanwhile, existing works do not consider that combining classified storage with special data structures to improve the efficiency of integrity check for outsourced EHRs. In this paper, we propose an efficient integrity check scheme for classified EHRs. First, our scheme not only protects the privacy of category information for EHRs, but also ensures the EHRs themselves. Second, we improve the performance of lookup and data updating dramatically by deploying adjustable-capacity cuckoo filter with a linked list, which is a container storing the EHRs' ciphertexts and verification metadata. Third, we implement our scheme in a more practical way by extending batch auditing of EHRs from single category to multi-category. The provable update for the cloud service provider and the third-party auditor after updating EHRs is also guaranteed. Finally, the security of our scheme is proven, and numerical analyses and simulation experiments show that our scheme is efficient. (C) 2020 Elsevier Inc. All rights reserved.

Automated summary

This paper proposes an efficient integrity check scheme for classified EHRs, which protects the privacy of EHRs and improves efficiency by combining classified storage with special data structures, implementing batch auditing of EHRs across multiple categories.