Based on Private Matching and Min-attribute Generalization for Privacy Preserving in Cloud Computing

When our private data are out-sourced in cloud computing, we should guarantee the confidentiality and search ability of the private data. However, nowadays privacy preserving issues in the cloud have not been carefully explored at current stage. To relieve individuals´ concerns of their data privacy, this paper explores a new approach based on private matching and min-attribute generalization to solve the problem of privacy preserving in the cloud. This paper also states the new problem of privacy indexing in the internet and proves that our proposed approach can avoid privacy indexing issue in the cloud.