数据前端加密是保护云环境下外包数据隐私的一种有效手段,但却给数据查询等操作带来挑战.针对云环境下多数据拥有者数据外包及选择性访问授权特征,为支持大规模加密云数据上高效且隐私保护的用户个性化密文查询,文中提出了一种隐私保护的高效密文排序查询方法RQED.通过设计无证书认证的PKES(支持关键词检索的公钥加密),并构建RQED框架来实现强隐私保护的密文查询.基于该框架,设计了更合理的多属性多关键词密文查询排序函数,并提出了基于层次动态布隆过滤器的RQED索引机制,提高密文查询时空效率.理论分析和实验性能对比证明:RQED在确保查询强隐私保护和高准确性的同时,具有较明显的时空效率优势.%In cloud computing, for protecting the privacy of the sensitive cloud data, an effective methodology is to encrypt the data before outsourcing. However, data encryption makes data utilization, e. g. querying, a very challenging task. Though many solutions have been proposed, they are insufficient or even ineffective to achieve efficient multi-keyword rank query and flexible selective query authorization with multiple data owners while keeping strong privacy preserving. In this paper, we propose an efficient privacy-preserving rank query over encrypted data (RQED). Through the improved searchable public key encryption (PKES) with certificateless authentication, we establish the RQED framework. Based on the RQED framework, we design a more sound and privacy-preserving RQED rank function, and propose a hierarchical index based on dynamic Bloom filters. The theoretical analysis and experimental evaluation show that the proposed solutions indeed achieve powerful privacy guarantee, efficient query performance, low communication overhead and effective query authorization control.
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