Evidence map›Paper›PMID 41271918›Full record

ArticleScientific reports2025

Quantum color image encryption using a novel 4D hyperchaotic Lorenz system and Fibonacci transform.

Saba Inam, Shamsa Kanwal, Rehana Amir, Amel Ksibi, Irum Matloob

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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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3 · Its place in the literature

Who cites it

5 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.
Rehana AmirDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan.
Amel KsibiDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Irum MatloobDepartment of Software Engineering, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Satellite images are critical for ecological monitoring and national security; thus, protecting its integrity is imperative. Nonetheless, existing encryption methods struggle to balance robustness and efficiency. This paper proposes a novel quantum chaos-based image encryption scheme (QCIES) combining a 4D hyperchaotic Lorenz system (4D-HLS) and quantum Fibonacci transform (QFT) addressing these limitations. During the encryption process, we first used The Generalized Quantum Image Representation (GQIR) technique to transform a conventional color image into quantum data. Then, 4D-HLS generates complex, unpredictable keys through bifurcation and sensitivity to initial conditions. 4D-HLS complex dynamics coupled with quantum pixel reorganization provide unprecedented resistance against statistical and brute-force attacks. Additionally, QFT with a quantum adder randomly encrypts pixel locations, producing the final encrypted image. Performance evaluation was conducted using Python to analyze key metrics including histogram distribution, information entropy, and adjacent pixel correlation. Extensive security testing revealed QCIES robust performance, achieving near-ideal correlation coefficients (< 0.004), information entropy (> 7.999), NPCR (99.64%), UACI (33.56%) and massive key space [Formula: see text]. The achieved [Formula: see text] key space notably exceeds the [Formula: see text] NIST standard, while maintaining computational efficiency through optimized quantum circuit design. These innovations establish a new benchmark for satellite image transmission in critical infrastructure applications.

Indexed as

Chaotic systemsFibonacci transformationQuantum addersQuantum circuitsQuantum image encryptionSecurity analysis

Identifiers

PMID41271918
PMCPMC12638871

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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.