Oblivious Multi-Keyword Search for Secure Cloud Storage Service
Rui Zhang, Rui Xue, Ling Liu, Lijuan Zheng · 2017
Outsource encrypted data has attracted attentions from industry and academics for storing sensitive data in third party clouds. Many cloud applications need privacy preserving multiple keywords search services over encrypted data with dual capabilities. On one hand, they need to keep the query keywords and associated search operations private such that data hosting service providers cannot trace and infer sensitive data stored in the third party data hosting servers. On the other hand, they need to support multiple keywords search to significantly improve the search efficiency. However, current keyword search protocols for encrypted data are not practical with poor privacy and low efficiency. In this paper, we propose a new oblivious multiple keywords search (OMKS) service, which provides privacy for both users and cloud storage service provider and supports efficient multiple keywords search. Compared to previous oblivious keyword search (OKS) protocols, our protocols maintain strong privacy, i.e., database security and query privacy, and effectively support disjunctive and conjunctive keywords search. The analysis and experiments show that OMKS protocols significantly reduce the storage and communication overhead. Moreover, the computation overhead of conjunctive search is not increased with the number of query keywords such that it can performs highly efficient conjunctive keywords search.