Measuring inference exposure in outsourced encrypted databases

Database outsourcing is becoming increasingly popular introducing a new paradigm, called database-as-a-service, where an encrypted client's database is stored at an external service provider. Existing proposals for querying encrypted databases are based on the association, with each encrypted tuple, of additional indexing information obtained from the plaintext values of attributes that can be used in the queries. However, the relationship between indexes and data should not open the door to inference and linking attacks that can compromise the protection granted by encryption. In this paper, we present a simple yet robust indexing technique and investigate quantitative measures to model inference exposure. We present different techniques to compute an aggregate measure from the infer- ence exposure associated with each single index. Our approach can take into account the importance of plaintext attributes associated with indexes and/or can allow the user to weight the inference exposure values supplied in relation to their relative ordering.