Evidence map›Paper›PMID 39994319›Full record

ArticleScientific reports2025

Cascading quantum walks with Chebyshev map for designing a robust medical image encryption algorithm.

Fahad Alblehai, Ahmed A Abd El-Latif, Paweł Pławiak, Bassem Abd-El-Atty

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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 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Fahad Alblehai *Computer Science Department, Community College, King Saud University, 11437, Riyadh, Saudi Arabia.
Ahmed A Abd El-Latif *Jadara University Research Center, Jadara University, Irbid, Jordan. a.rahiem@gmail.com.
Paweł Pławiak *Department of Computer Science, Faculty of Computer Science and Telecommunications, Cracow University of Technology, Warszawska 24, 31-155, Krakow, Poland.
Bassem Abd-El-Atty *Department of Computer Science, Faculty of Computers and Information, Luxor University, Luxor, 85957, Egypt. bassem.abdelatty@fci.luxor.edu.eg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The secure storage and transmission of healthcare data have become a critical concern due to their increasing use in the diagnosis and treatment of various diseases. Medical images contain confidential patient information, and unauthorized access to or modification of these images can have severe consequences. Chaotic maps are commonly used for constructing medical image cipher systems, but with the growth of quantum technology, these systems may become vulnerable. To address this issue, a new medical image cipher algorithm based on cascading quantum walk with Chebyshev map has been presented in this paper. The proposed system has been tested and found to have high levels of security and efficiency, with UACI, NPCR, Chi-square, and global information entropy values averaging at 33.48095%, 99.62984%, 248.92128, and 7.99923, respectively.

Indexed as

AlgorithmsComputer SecurityDiagnostic ImagingImage Processing, Computer-AssistedHumans

Identifiers

PMID39994319
PMCPMC11850827

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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.