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Related Experiment Video

Updated: Sep 18, 2025

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
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Enhancing medical image privacy in IoT with bit-plane level encryption using chaotic map.

Fatima Asiri1, Wajdan Al Malwi1, Tamara Zhukabayeva2

  • 1Informatics and Computer Systems Department, College of Computer Science, King Khalid University, Abha, Saudi Arabia.

Frontiers in Computational Neuroscience
|June 23, 2025
PubMed
Summary

A new bit plane encryption method secures medical images for IoT devices. This novel approach enhances privacy and offers strong resilience against attacks, ideal for resource-limited smart devices.

Keywords:
Chen chaotic mapIoTbit-level encryptionchaosimage encryptionmeaningful encryption

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Area of Science:

  • Medical Imaging
  • Cybersecurity
  • Internet of Things (IoT)

Background:

  • Privacy preservation is crucial for medical imaging, particularly on resource-constrained IoT devices.
  • Existing encryption methods may not be efficient for edge computing environments.

Purpose of the Study:

  • To develop a novel, bit plane-level encryption method for medical images tailored for IoT environments.
  • To enhance the security and privacy of sensitive medical data transmitted and stored on smart devices.

Main Methods:

  • Utilized Secure Hash Algorithm (SHA) and Chen chaotic map for generating random number vectors.
  • Employed bit plane shuffling and diffusion using generated random vectors.
  • Embedded the encrypted image into a carrier image for visual security.

Main Results:

  • Demonstrated high resilience to attacks through correlation coefficient, histogram, and entropy analyses.
  • Achieved a large key space of (10^90)^8 and strong sensitivity.
  • Evaluated performance via occlusion analysis, confirming robustness.

Conclusions:

  • The proposed encryption scheme is highly resilient and suitable for resource-limited IoT devices.
  • Effectively addresses privacy concerns in medical imaging within the IoT context.