Evidence map›Paper›PMID 34828218›Full record

ArticleEntropy (Basel, Switzerland)2021

A Quantum Blind Multi-Signature Method for the Industrial Blockchain.

Zhengying Cai, Shi Liu, Zhangyi Han, Rui Wang, Yuehua Huang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Zhengying CaiCollege of Computer and Information Technology, China Three Gorges University, Yichang 443002, China.
Shi LiuCollege of Computer and Information Technology, China Three Gorges University, Yichang 443002, China.
Zhangyi HanCollege of Computer and Information Technology, China Three Gorges University, Yichang 443002, China.
Rui WangCollege of Computer and Information Technology, China Three Gorges University, Yichang 443002, China.ORCID 0000-0002-3785-6529
Yuehua HuangCollege of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China.

Funding

Major Science And Technology Projects in Hubei Province of China 2020AEA012National Natural Science Foundation of China 71471102
6 · The paper itself

Abstract

Traditional anti-quantum methods and multi-signature technologies to secure the blockchain against quantum attacks will quickly reduce the efficiency and scalability of the industrial blockchain, where the computational resources will experience a polynomial rise with the increasing number of traders. Here, a quantum blind multi-signature method is proposed for the multi-party transaction to provide anti-quantum security. First, the proposed multi-party transaction frame and quantum key distribution in the industrial blockchain are introduced. It integrates a novel quantum blind multi-signature algorithm that is based on the quantum entanglement mechanism, and it is absolutely secure in theory. Second, the anti-quantum multi-signature algorithm is illustrated, where there are four phases, i.e., initialization, signing, verification, and implementation. Third, the security and complexity of the proposed framework are analyzed and compared with related methods in references, and our proposed method is verified to be able to offer good computational performance and blockchain scalability for multi-party transaction. Last, the paper is summarized and future research directions are proposed.

Indexed as

anti-quantumindustrial blockchainmulti-party transactionquantum blind multi-signature

Identifiers

PMID34828218
PMCPMC8622831

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.