Privacy-Preserving Queries for a DAS Model Using Encrypted Bloom Filter

Abstract

Recently, Database-As-a-Service (DAS) has attracted considerable attention. Users require protecting sensitive data from the DAS administrators. Most of previous studies, which proposed the solutions using cryptographic techniques, assume that a large amount of data will be inserted into the database and new data will be uploaded infrequently. We propose a secure query execution model for such an environment. Our approach is to represent all schemes of each tuple in a plaintext table as one Bloom filter index, and to replace queries with keyword searches of the Bloom filter index. Same values in each tuple are transformed into different values by two-phase encryption. DAS administrators cannot determine the schemes of the original table even if they look view the database and queries. Therefore, our approach is robust against the estimation of schemes in original tables.