[Show abstract][Hide abstract] ABSTRACT: Database as a Service (DaaS), a form of cloud computing, has recently attracted considerable attention. Users require their sensitive data to be protected from a database administrator that serves as a third party managing the data. We have proposed a secure query execution model for such an environment [10, 11]. Key features of our approach are to represent each tuple of each scheme as a plaintext table with one bloom filter index and to replace queries with keyword searches of the bloom filter index. In , we have defined an attack model in which attackers guess features of a plaintext table by observing bit patterns of the bloom filter index: further, we considered a defense against such as attack. We must also assume in this model that attackers can access query logs and may infer features of a plaintext table using such query logs. In this paper, we define an attack model by using query logs and propose a method to defend against the attack by executing fake queries.
[Show abstract][Hide abstract] 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.