Evidence map›Paper›PMID 38437206›Full record

ArticlePloS one2024

BPKEM: A biometric-based private key encryption and management framework for blockchain.

Hao Cai, Han Li, Jianlong Xu, Linfeng Li, Yue Zhang

Abstract read
In one paragraph

Article in PloS one, 2024. 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.

Hao CaiDepartment of Computer Science, Shantou University, Shantou, China.
Han LiDepartment of Computer Science, Shantou University, Shantou, China.ORCID 0000-0002-3262-7313
Jianlong XuDepartment of Computer Science, Shantou University, Shantou, China.ORCID 0000-0003-2826-9282
Linfeng LiDepartment of Computer Science, Shantou University, Shantou, China.
Yue ZhangDepartment of Computer Science, Shantou University, Shantou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fundamental technology behind bitcoin, known as blockchain, has been studied and used in a variety of industries especially in finance. The security of blockchain is extremely important as it will affects the assets of the clients as well as it is the lifeline feature of the entire system that needs to be guaranteed. Currently, there is a lack of a methodical approach to guarantee the security and dependability of the private key during its whole life. Furthermore, there is no quick, easy, or secure way to create the encryption key. A biometric-based private key encryption and management framework (BPKEM) for blockchain is proposed not only to solve the private key lifecycle manag- ement problem, but also it maintains compatibility with existing blockchain systems. For the problem of private key encryption, a biometric-based stable key generation method is proposed. By using the relative invariance between facial and fingerprint feature points, this measure can convert feature points into stable and distinguishable descriptors, then using a reusable fuzzy extractor to create a stable key. The correct- ness and efficiency of the newly proposed biometric-based blockchain encryption tech- nique in this paper has been validated in the experiments.

Indexed as

BlockchainBiometryFaceHumansIndustryMaintenance

Identifiers

PMID38437206
PMCPMC10911611

What OpenQuestion holds

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LicenceCC BY
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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.