A multi-keyword parallel ciphertext retrieval scheme based on inverted index under the robot distributed system

Authors

DOI:

https://doi.org/10.4108/eai.17-12-2021.172438

Keywords:

ciphertext retrieval, multi-keyword parallel retrieval system, inverted index

Abstract

We, the Publisher, have retracted the following article: Jiyue Wang, Xi Zhang, Yonggang Zhu (2022). A multi-keyword parallel ciphertext retrieval scheme based on inverted index under the robot Distributed system. EAI Endorsed Scal Inf Syst. http://dx.doi.org/10.4108/eai.17-12-2021.172438

The traditional ciphertext retrieval scheme has some problems, such as low retrieval performance, lack of single keyword retrieval mode and limitation of single machine resources in traditional single server architecture. At the same time, for searchable encryption, it needs to balance the data security and retrieval efficiency. In this paper, a multi-keyword parallel ciphertext retrieval system based on inverted index is proposed. The system adopts different index encryption methods to improve the performance of ciphertext retrieval. Through the segmentation of ciphertext inverted index, the block retrieval of inverted index is realized, which overcomes the limitation of single machine resources and improves the retrieval efficiency. By combining the characteristics of distribution, the traditional single-machine retrieval architecture is extended and multi-keyword parallel retrieval is realized. The experimental results show that compared with SSE-1 scheme, the proposed scheme can improve the efficiency of retrieval, update and other operations on the premise of ensuring the security of ciphertext data, achieve multi-keyword retrieval, and dynamically expand the distributed architecture of the system. Finally, it can improve the system load capacity.

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Published

17-12-2021

How to Cite

1.
Wang J, Zhang X, Zhu Y. A multi-keyword parallel ciphertext retrieval scheme based on inverted index under the robot distributed system. EAI Endorsed Scal Inf Syst [Internet]. 2021 Dec. 17 [cited 2024 Nov. 22];9(36):e12. Available from: https://publications.eai.eu/index.php/sis/article/view/317