Kirchhoff Law Johnson noise key generation for secure decentralized identifiers.

Kamalesh Mohanasundar, Sarah A Flanery, Srujan Kotikela, Christiana Chamon

Abstract read

In one paragraph

Article in Scientific reports, 2026. 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

4 authors.

Kamalesh MohanasundarDepartment of Computer Science, University of Texas at Dallas, Richardson, 75080, TX, USA.

Sarah A FlaneryDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, 77843, TX, USA.

Srujan KotikelaDepartment of Information and Operations Management, Texas A&M University, College Station, TX, 77843, USA.

Christiana ChamonDepartment of Electrical and Computer Engineering, Virginia Tech, Blacksburg, 24060, VA, USA. ccgarcia@vt.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper experimentally integrates an existing Kirchhoff-Law-Johnson-Noise (KLJN) physical key exchange scheme as a source of truly random keys for decentralized identifiers (DIDs). Web 3.0 is driven by secure keys, typically represented in hexadecimal, that are pseudo-randomly generated by an initialization vector and complex computational algorithms. We demonstrate that the statistical physical KLJN scheme eliminates the additional computational power by naturally generating physically random binary keys to drive the creation of DIDs that are appended to an Ethereum blockchain.

Identifiers

PMID41507266

DOI10.1038/s41598-025-34403-7

PMCPMC12864867

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LicenceCC BY

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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.