Enhancing medical image privacy in IoT with bit-plane level encryption using chaotic map
Extensive evaluations have proven that the designed scheme exhibits a high degree of resilience to attacks, making it particularly suitable for small IoT devices with limited processing power and memory.
Authors
- Abdullah Nur Aziz (ORCID: https://orcid.org/0000-0003-4684-4682)
- Fatima Asiri (ORCID: https://orcid.org/0009-0000-4296-9483)
- Abdullah Qayyum (ORCID: https://orcid.org/0000-0002-0132-1039)
- Tamara Zhukabayeva (ORCID: https://orcid.org/0000-0001-6345-5211)
- Ibtehal Nafea
- Nadhmi A. Gazem
- Wajdan Al Malwi
Institutions
- L. N. Gumilyov Eurasian National University (KZ)
- University of Sussex (GB)
- Taibah University (SA)
- University Hospital of Umeå (SE)
- University of Business and Technology (SA)
- King Khalid University (SA)
- Umeå University (SE)
Publication Details
- Journal
- Frontiers in Computational Neuroscience
- Published
- 2025-06-06
- DOI
- https://doi.org/10.3389/fncom.2025.1591972
- Citations
- 5
- Primary Topic
- Chaos-based Image/Signal Encryption
- Type
- article
- Field-Weighted Citation Impact
- 6.38