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Verifiable Diversity Ranking Search Over Encrypted Outsourced Data

Yuling Liu1,*, Hua Peng1, Jie Wang2

College of Computer Science and Electronic Engineering, Hunan University, Lushan South Road No. 2, Changsha, Hunan, China, 410082.
Department of Computer Science, University of Massachusetts Lowell, One University Avenue, Lowell, M. A., USA, 01854.

* Corresponding author: Yuling Liu. Email: email.

Computers, Materials & Continua 2018, 55(1), 37-57.


Data outsourcing has become an important application of cloud computing. Driven by the growing security demands of data outsourcing applications, sensitive data have to be encrypted before outsourcing. Therefore, how to properly encrypt data in a way that the encrypted and remotely stored data can still be queried has become a challenging issue. Searchable encryption scheme is proposed to allow users to search over encrypted data. However, most searchable encryption schemes do not consider search result diversification, resulting in information redundancy. In this paper, a verifiable diversity ranking search scheme over encrypted outsourced data is proposed while preserving privacy in cloud computing, which also supports search results verification. The goal is that the ranked documents concerning diversification instead of reading relevant documents that only deliver redundant information. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is effective for the diversification of documents and verification.


Cite This Article

APA Style
Liu, Y., Peng, H., Wang, J. (2018). Verifiable diversity ranking search over encrypted outsourced data. Computers, Materials & Continua, 55(1), 37-57.
Vancouver Style
Liu Y, Peng H, Wang J. Verifiable diversity ranking search over encrypted outsourced data. Comput Mater Contin. 2018;55(1):37-57
IEEE Style
Y. Liu, H. Peng, and J. Wang "Verifiable Diversity Ranking Search Over Encrypted Outsourced Data," Comput. Mater. Contin., vol. 55, no. 1, pp. 37-57. 2018.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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