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Open AccessArticle

Public Key Encryption with Keyword Search in Cloud: A Survey

1
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
2
School of Cyber Security, Gansu University of Political Science and Law, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(4), 421; https://doi.org/10.3390/e22040421
Received: 5 March 2020 / Revised: 1 April 2020 / Accepted: 5 April 2020 / Published: 8 April 2020
(This article belongs to the Section Information Theory, Probability and Statistics)
With the popularization of cloud computing, many business and individuals prefer to outsource their data to cloud in encrypted form to protect data confidentiality. However, how to search over encrypted data becomes a concern for users. To address this issue, searchable encryption is a novel cryptographic primitive that enables user to search queries over encrypted data stored on an untrusted server while guaranteeing the privacy of the data. Public key encryption with keyword search (PEKS) has received a lot of attention as an important branch. In this paper, we focus on the development of PEKS in cloud by providing a comprehensive research survey. From a technological viewpoint, the existing PEKS schemes can be classified into several variants: PEKS based on public key infrastructure, PEKS based on identity-based encryption, PEKS based on attribute-based encryption, PEKS based on predicate encryption, PEKS based on certificateless encryption, and PEKS supporting proxy re-encryption. Moreover, we propose some potential applications and valuable future research directions in PEKS. View Full-Text
Keywords: cloud computing; searchable encryption; search query; public key encryption with keyword search; data privacy cloud computing; searchable encryption; search query; public key encryption with keyword search; data privacy
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Zhou, Y.; Li, N.; Tian, Y.; An, D.; Wang, L. Public Key Encryption with Keyword Search in Cloud: A Survey. Entropy 2020, 22, 421.

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