Top-k Query Processing on Encrypted Databases with Strong Security Guarantees
Xianrui Meng, Haohan Zhu, George Kollios · 2018
Concerns about privacy in outsourced cloud databases have grown recently and many efficient and scalable query processing methods over encrypted data have been proposed. However, there is very limited work on how to securely process top-k ranking queries over encrypted databases in the cloud. In this paper, we propose the first efficient and provably secure top-k query processing construction that achieves adaptive CQA security. We develop an encrypted data structure called EHL and describe several secure sub-protocols under our security model to answer top-k queries. Furthermore, we optimize our query algorithms for both space and time efficiency. Finally, we empirically evaluate our protocol using real world datasets and demonstrate that our construction is efficient and practical.