Quantum Image Encryption using Quantum Image Representations

Since their introduction, numerous quantum image encryption methods have been developed. As we shall demonstrate, protecting visual information against classical and quantum threats depends on representations. In this paper, we identify the essential components of quantum encryption algorithms and explain a variety of quantum image representations with different levels of qubit efficiency, computational complexity, and security. The paper also explores the favourable and unfavourable aspects of hybrid, chaos-based, quantum transform-based, and DNA-based quantum image encryption schemes. The security analysis focuses on noise tolerance and scalability. This involves aspects such as key space size, resistance to various attacks, and calculation efficiency. Meanwhile, potential areas for investigation include robust algorithms, hybrid systems and reducing decoding errors. We also address the implementation difficulties involved, including the necessary hardware and decoding error reduction. Classical and quantum techniques, as well as more advanced quantum equipment, are considered too. The evaluation calls for uniform policies and realistic responses and emphasises how quantum image encryption could transform information security in the quantum era. and realistic answers and highlights how quantum image encryption may change information safety within the quantum generation.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-02-03
DOI
https://doi.org/10.1051/epjconf/202635001001/pdf
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum Image Encryption using Quantum Image Representations

Achraf Abdelghafour Zemate, Moulay Brahim Sedra
Springer Link (Chiba Institute of Technology)
Chaos-based Image/Signal Encryption
article

Quantum Image Encryption using Quantum Image Representations

Achraf Abdelghafour Zemate, Moulay Brahim Sedra
article en

Abstract

Since their introduction, numerous quantum image encryption methods have been developed. As we shall demonstrate, protecting visual information against classical and quantum threats depends on representations. In this paper, we identify the essential components of quantum encryption algorithms and explain a variety of quantum image representations with different levels of qubit efficiency, computational complexity, and security. The paper also explores the favourable and unfavourable aspects of hybrid, chaos-based, quantum transform-based, and DNA-based quantum image encryption schemes. The security analysis focuses on noise tolerance and scalability. This involves aspects such as key space size, resistance to various attacks, and calculation efficiency. Meanwhile, potential areas for investigation include robust algorithms, hybrid systems and reducing decoding errors. We also address the implementation difficulties involved, including the necessary hardware and decoding error reduction. Classical and quantum techniques, as well as more advanced quantum equipment, are considered too. The evaluation calls for uniform policies and realistic responses and emphasises how quantum image encryption could transform information security in the quantum era. and realistic answers and highlights how quantum image encryption may change information safety within the quantum generation.

Springer Link (Chiba Institute of Technology)
Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Chaos-based Image/Signal Encryption
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.