Int. J. of Web and Grid Services   »   2018 Vol.14, No.1

 

 

Title: Key-aggregate searchable encryption under multi-owner setting for group data sharing in the cloud

 

Authors: Tong Li; Zheli Liu; Chunfu Jia; Zhangjie Fu; Jin Li

 

Addresses:
College of Computer and Control Engineering, Nankai University, No. 38 Tongyan Road, Jinnan District, Tianjin, China
College of Computer and Control Engineering, Nankai University, No. 38 Tongyan Road, Jinnan District, Tianjin, China; Nanjing University of Information Science & Technology (NUIST), Nanjing, China
College of Computer and Control Engineering, Nankai University, No. 38 Tongyan Road, Jinnan District, Tianjin, China
School of Computer and Software, Nanjing University of Information Science & Technology (NUIST), Nanjing, China
School of Computer Science, Guangzhou University, Guangzhou, China.

 

Abstract: In recent years, the encryption with keyword search has been widely used in cloud data sharing system to protect privacy and confidentiality when the ciphertext is retrieving. However, selectively sharing encrypted data and related searching abilities among different users via the existing searchable encryption technology certainly will generate a large number of searching trapdoors making the system inflexible and impractical. In this paper, we propose the concept of "multi-owner key-aggregate searchable encryption" scheme and its implementation, in which a user can only submit a trapdoor for querying the documents shared by multiple owners who only need to distribute an aggregate key for sharing massive data. Thus, the scheme supports effective data sharing for both multiple owners and users by reducing unnecessary trapdoors which are hard for generating by mobile devices during the querying step. Finally we conduct security analysis and performance evaluation which can show that our system is practical and secure.

 

Keywords: cloud storage; data sharing; key-aggregate; searchable encryption.

 

DOI: 10.1504/IJWGS.2018.10008981

 

Int. J. of Web and Grid Services, 2018 Vol.14, No.1, pp.21 - 43

 

Available online: 13 Nov 2017

 

 

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