Privacy Preserving Query over Encrypted Multidimensional Massive Data in Cloud Storage

Abstract

Cloud storage is widely used in massive data outsourcing, but how to efficiently query encrypted multidimensional data stored in an untrusted cloud environment remains a research challenge. We propose a high performance and privacy-preserving query (pLSH-PPQ) scheme over encrypted multidimensional data to address this challenge. In our scheme, for a given query, the proxy server will return K top similar data object identifiers. An enhanced Ciphertext-Policy Attribute-Based Encryption (CP-ABE) policy is used to control access to the search results. Therefore, only the requester with the permission attribute can obtain correct secret keys to decrypt the data. Security analysis proves that the pLSH-PPQ scheme achieves data confidentiality and reserves the data owner’s privacy in a semi-trusted cloud. In addition, evaluations demonstrate that the pLSH-PPQ scheme can significantly reduce response time and provide high search efficiency without compromising on search quality.