Evidence map›Paper›PMID 33291483›Full record

ArticleSensors (Basel, Switzerland)2020

A Multi-User Public Key Encryption with Multi-Keyword Search out of Bilinear Pairings.

Shuo Zhang, Qiaoyan Wen, Wenmin Li, Hua Zhang, Zhengping Jin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shuo ZhangState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.ORCID 0000-0001-5362-8916
Qiaoyan WenState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Wenmin LiState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Hua ZhangState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Zhengping JinState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Funding

National Natural Science Foundation of China 61502044
6 · The paper itself

Abstract

Internet of Things (IoT) and cloud computing are adopted widely in daily life and industrial production. Sensors of IoT equipment gather personal, sensitive and important data, which is stored in a cloud server. The cloud helps users to save cost and collaborate. However, the privacy of data is also at risk. Public-key encryption with keyword search (PEKS) is convenient for users to use the data without leaking privacy. In this article, we give a scheme of PEKS for a multi-user to realize the multi-keyword search at once and extend it to show a rank based on keywords match. The receiver can finish the search by himself or herself. With private cloud and server cloud, most users' computing can be outsourced. Moreover, the PEKS can be transferred to a multi-user model in which the private cloud is used to manage receivers and outsource. The store cloud and the private cloud both obtain nothing with the keyword information. Then our IoT devices can easily run these protocols. As we do not use any pairing operations, the scheme is under more general assumptions that means the devices do not need to take on the heavy task of calculating pairing.

Indexed as

multi-keywordmulti-userPEKSpublic key encryption with keyword search

Identifiers

PMID33291483
PMCPMC7730920

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.