Cited by 54Chaos-based Image/Signal EncryptionComputer Science and EngineeringCryptography and Data Security

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An improved chaotic image encryption algorithm using Hadoop-based MapReduce framework for massive remote sensed images in parallel IoT applications

Al-Khasawneh, Mahmoud Ahmad, Uddin, Irfan, Shah, Syed Atif Ali, Khasawneh, Ahmad M., Abualigah, Laith, Mahmoud, Marwan·2022·Cluster Computing

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Crossref · 10.1007/s10586-021-03466-2

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  • The single-kernel encryption scheme is advantageous for bulk-image applications because different available kernels can encrypt different images with no data dependency between images.

    “Another advantage of the single kernel encryption scheme is for bulk-images application [2], when the different available kernels can be used to encrypt different images, as there is no data dependency between different images.”

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Research works printed but not linked: 54

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Metadata

Authors
Al-Khasawneh, M. A., Uddin, I., Shah, S. A. A., Khasawneh, A. M., Abualigah, L., & Mahmoud, M.
Affiliations
  • Skyline University College (AE)
  • Amman Arab University (JO)
  • King Abdulaziz University (SA)
Corresponding author
Khasawneh, Ahmad M.
Venue
Cluster Computing
Published
2021-11-30
Volume
25
Issue
2
Pages
999-1013
ISSN
  • 1386-7857 (ISSN-L)
  • 1573-7543
OpenAlex
W3216230586
Cited by
54
References
1
Citations by year
2026: 6 · 2025: 6 · 2024: 11 · 2023: 23 · 2022: 8
FWCI
3.78
Type
journal article
Language
en
Open access
closed
Locations
Cluster Computing (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
  • Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
  • Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
Keywords
chaotic image encryption, remote sensing images, Hadoop, MapReduce, parallel encryption, Henon map, logistic map, Gauss map, GeoTIFF, Internet of Things

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