Evidence map›Paper›PMID 40038335›Full record

ArticleScientific reports2025

A blockchain-integrated chaotic fractal encryption scheme for secure medical imaging in industrial IoT settings.

Saba Inam, Shamsa Kanwal, Mamoona Batool, Shaha Al-Otaibi, Mona M Jamjoom

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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.

Saba InamDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan. saba.inam@fjwu.edu.pk.
Shamsa KanwalDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan.
Mamoona BatoolDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan.
Shaha Al-OtaibiDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, 11671, Riyadh, Saudi Arabia.
Mona M JamjoomDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, 11671, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing adoption of smart cameras and image sensors in industrial and medical applications necessitates robust visual data security solutions. The industrial Internet of Things (IoT) introduces unique security challenges, particularly due to third-party involvement, which undermines traditional security mechanisms. This study presents a three-layered encryption scheme integrating novel blockchain technology with chaotic fractal image encryption scheme to address these challenges. The encryption process combines an S-box generated from the May map for pixel substitution with fractal-based key generation using a logistic map-driven Sierpinski triangle and incorporates a Chebyshev map-based diffusion step for enhanced randomness and security. Extensive testing, including key sensitivity analysis, entropy calculations (average entropy: 7.9998), NPCR (99.92%), UACI (33.31%), and PSNR values (29.74 dB for encrypted images), validates the scheme's robustness. The results confirm high resistance to differential and brute-force attacks, making the scheme highly suitable for securing sensitive medical images in IoT environments while ensuring confidentiality and integrity.

Indexed as

Blockchain technologyChaotic mapFractal-based key generationImage encryptionIoT securityMay mapMedical image securityS-box

Identifiers

PMID40038335
PMCPMC11880370

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LicenceCC BY-NC-ND
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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.