A Reinforced Dynamic Multi-keyword Ranked Search with Forward Privacy

Chien-Ming Chen, Zhuoyu Tie, Eric Ke Wang, Kuo-Hui Yeh, Wensheng Gan, SK Hafizul Islam

Abstract: Searchable symmetric encryption performs satisfactorily in protecting the privacy of outsourced data in cloud storage scenarios because it encrypts data and provides a secure way of searching on the ciphertext. Dynamic searchable symmetric encryption is designed to support insertion and deletion of outsourced data. However, insertion may cause information leakage of updated keywords. Thus, forward privacy is proposed to limit the leakage of insertion, and it has become an important security attribute for dynamic schemes. The existing dynamic searchable symmetric encryption schemes with forward privacy are mainly based on two approaches, re-build index with fresh key and token with state information. However, both approaches have their constraint and advantages. In this paper, we first proposed a new highly versatile reinforcement approach. The proposed approach is easy to implement. Besides, we minimized the loss of efficiency by setting a small threshold value. In order to demonstrate that the proposed approach is effective, we utilize our approaches to improve EDMRS scheme. Security and performance analysis show that the improved scheme with the proposed approach is still satisfy the forward privacy without a significant loss of performance.