Towards efficient privacy-preserving conjunctive keywords search over encrypted cloud data

Abstract

With increasing popularity of cloud computing, more and more users choose to store data on cloud servers. Privacy-preserving keyword search is a critical technology in the field of cloud computing, which can directly search for encrypted data stored on cloud servers. In this paper, we propose a new scheme which can achieve conjunctive keywords search in a privacy-preserving way, and maintain forward security. In order to realize conjunctive keywords search with reduced communication cost and leakage, our scheme constructs a secure index based on the full binary tree data structure. Each leaf node represents a keyword, and the node stores the file identifier containing the keyword. Thus, all files containing searched keywords can be searched at one time without searching one file by one. The search time is only related to the number of search keywords and not related to the number of files. Each non-leaf node stores the keywords of its left and right child nodes, which are mapped to the Indistinguishable Bloom Filter(IBF). To achieve forward security, we choose a random string as the latest state to update trapdoors for each update query. Thus, update trapdoor cannot match with previous search trapdoors to achieve forward security. Finally, detailed experiments and security analysis prove that our scheme is secure and efficient.