Evidence map›Paper›PMID 40414972›Full record

ArticleScientific reports2025

Secure medical image encryption with hyperelliptic curve based S-boxes.

Amal S Alali, Rashad Ali, Muhammad Kamran Jamil, Javed Ali, Gulraiz

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Amal S AlaliDepartment of Mathematical Sciences, College of Science, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Rashad AliDepartment of Mathematics, Riphah International University, Lahore, Pakistan.
Muhammad Kamran JamilDepartment of Mathematics, Riphah International University, Lahore, Pakistan. m.kamran.sms@gmail.com.
Javed AliDepartment of Mathematics, Riphah International University, Lahore, Pakistan.
GulraizDepartment of Mathematics, Riphah International University, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two fundamental prerequisites are needed for symmetric encryption techniques. Diffusion is the first of them. Confusion is the most significant and second factor. Substitution box (S-box) structure in these algorithms typically satisfies this condition. S-box architectures need to be robust as a result. The encryption procedure will therefore be hard to crack if the S-box is cryptographically sound. Getting a powerful S-box, however, is a challenging issue. Recent research has demonstrated that the security of a cryptosystem may be significantly improved by switching from static to dynamic S-boxes. Consequently, it is now essential to create new, secure S-boxes. In this paper, we proposed a practical method for generating dynamic S-boxes using a specific class of hyperelliptic curves defined over prime fields. The method involves selecting a large prime number and a random integer as parameters, iterating through candidate points on the curve, and applying a filtering condition to extract valid points. These points are then processed using a two-dimensional function and modular reduction to produce a list of unique values. If 256 unique values are obtained, they are reshaped into a [Formula: see text] S-box matrix. Computational results show that our approach can produce cryptographically robust S-boxes with a security level similar to certain existing S-boxes constructed using alternative mathematical structures. Compared to alternative solutions, our S-box exhibits exceptional non-linearity and resilience, effectively fending off both linear and differential assaults. The results of our investigation highlight how well this hyperelliptic curve-based S-box works to improve medical picture security.

Indexed as

ECCEntropyHyperelliptic curvesImage encryptionSubstitution box

Identifiers

PMID40414972
PMCPMC12104349

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.