Biblio

To ensure a secure Cloud-based Electronic Health Record (EHR) system, we need to encrypt data and impose field-level access control to prevent malicious usage. Since the attributes of the Users will change with time, the encryption policies adopted may also vary. For large EHR systems, it is often necessary to search through the encrypted data in realtime and perform client-side computations without decrypting all patient records. This paper describes our novel cloud-based EHR system that uses Attribute Based Encryption (ABE) combined with Semantic Web technologies to facilitate differential access to an EHR, thereby ensuring only Users with valid attributes can access a particular field of the EHR. The system also includes searchable encryption using keyword index and search trapdoor, which allows querying EHR fields without decrypting the entire patient record. The attribute revocation feature is efficiently managed in our EHR by delegating the revision of the secret key and ciphertext to the Cloud Service Provider (CSP). Our methodology incorporates advanced security features that eliminate malicious use of EHR data and contributes significantly towards ensuring secure digital health systems on the Cloud.

Recently there has been much interest in performing search queries over encrypted data to enable functionality while protecting sensitive data. One particularly efficient mechanism for executing such queries is order-preserving encryption/encoding (OPE) which results in ciphertexts that preserve the relative order of the underlying plaintexts thus allowing range and comparison queries to be performed directly on ciphertexts. Recently, Popa et al. (SP 2013) gave the first construction of an ideally-secure OPE scheme and Kerschbaum (CCS 2015) showed how to achieve the even stronger notion of frequency-hiding OPE. However, as Naveed et al. (CCS 2015) have recently demonstrated, these constructions remain vulnerable to several attacks. Additionally, all previous ideal OPE schemes (with or without frequency-hiding) either require a large round complexity of O(log n) rounds for each insertion, or a large persistent client storage of size O(n), where n is the number of items in the database. It is thus desirable to achieve a range query scheme addressing both issues gracefully. In this paper, we propose an alternative approach to range queries over encrypted data that is optimized to support insert-heavy workloads as are common in "big data" applications while still maintaining search functionality and achieving stronger security. Specifically, we propose a new primitive called partial order preserving encoding (POPE) that achieves ideal OPE security with frequency hiding and also leaves a sizable fraction of the data pairwise incomparable. Using only O(1) persistent and O(ne) non-persistent client storage for 0(1-e)) search queries. This improved security and performance makes our scheme better suited for today's insert-heavy databases.