A New Query Integrity Verification Method with Cluster-based Data Transformation in Cloud Computing Environment

Due to advancement in cloud computing technology, the research on the outsourced database has been spotlighted. In database outsourcing, because the service provider might be untrusted or compromised, two issues of data security emerge: data confidentiality and data integrity. Many data transformation schemes were widely studied for preserving data confidentiality, but they are vulnerable to data leakage problem because they do not consider data distribution when encrypting original data. Meanwhile, several query authentication schemes were proposed to verity data integrity, but they suffer from transmission overhead of verification data. Motivated by these problems, we propose a privacy-aware query authentication scheme which guarantees the data confidentiality and the query result integrity of sensitive data. To solve the original data leakage problem, our clustering-based data transformation scheme is designed to select anchors based on data distribution. To verify the query result, we propose a query result authentication index that stores an encrypted signature for each anchor, which is a concatenated hash digest of cluster data. A user compares the verification information with the cluster signatures stored in the verification index. Through performance evaluation, we show that our method outperforms the existing method in terms of query processing time and verification data size.