Chaos-driven encryption of biomedical EEG using fractional-order memristive dynamics and random quantization
Huda M Alshanbari1, Sara Alluhaidan2, Aljazi Naif2
1Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Scientific Reports
|July 7, 2026
Summary
This study introduces a novel EEG encryption method using a fractional variable-order memristive hyperchaotic system. The advanced system ensures highly secure, unpredictable electroencephalogram (EEG) data encryption with minimal distortion.
Area of Science:
- Cryptography
- Biomedical Signal Processing
- Nonlinear Dynamics
Background:
- Electroencephalogram (EEG) data security is critical for privacy.
- Existing encryption methods may lack sufficient complexity for sensitive biological signals.
- Hyperchaotic systems offer potential for robust cryptographic applications.
Purpose of the Study:
- To develop a secure and efficient encryption framework for multi-channel EEG signals.
- To design a novel fractional variable-order memristive hyperchaotic system for generating high-entropy keystreams.
- To validate the security and performance of the proposed EEG encryption scheme.
Main Methods:
- A new fractional variable-order memristive hyperchaotic system was designed.
- A nonlinear keystream generator was constructed using chaotic state mixing and Boolean operations.
- A lightweight byte-wise XOR encryption architecture was applied to EEG signals.
- Extensive security analyses, including NIST randomness tests and PRD distortion analysis, were performed.
Main Results:
- The proposed system generated highly random keystreams passing all NIST statistical tests.
- The encryption scheme demonstrated excellent diffusion capabilities (NPCR=99.57%, UACI=33.656%).
- Negligible reconstruction distortion (PRD < 1%) was observed across 20 EEG channels.
- The encryption significantly enhanced EEG signal security compared to conventional methods.
Conclusions:
- The developed fractional variable-order memristive hyperchaotic system provides a robust foundation for secure EEG encryption.
- The proposed framework offers a highly secure, efficient, and low-distortion solution for protecting sensitive EEG data.
- This approach significantly advances the state-of-the-art in chaos-based cryptography for biomedical applications.
