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SAEF: Secure Anonymization and Encryption Framework for Open-Access Remote Photoplethysmography Datasets.

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    This study introduces a privacy framework for remote photoplethysmography (rPPG) datasets, enabling open access. The secure anonymization and encryption framework (SAEF) removes sensitive facial data with minimal impact on signal quality, enhancing data security and usability.

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    Area of Science:

    • Biomedical Engineering
    • Computer Science
    • Data Privacy

    Background:

    • Advancements in remote photoplethysmography (rPPG) technology are crucial for non-invasive physiological monitoring.
    • Current rPPG datasets face significant privacy challenges due to reliance on facial features, limiting open-access initiatives.
    • Protecting sensitive facial data is paramount for ethical dataset development and widespread adoption.

    Purpose of the Study:

    • To establish privacy protection principles for rPPG datasets.
    • To introduce a secure anonymization and encryption framework (SAEF) for rPPG data.
    • To enable the creation of volunteer-friendly, open-access rPPG datasets without compromising data integrity.

    Main Methods:

    • Developed SAEF to identify and remove privacy-sensitive facial regions using importance and necessity analysis.
    • Implemented an irreversible facial region removal process with minimal impact on rPPG signal quality.
    • Introduced a high-efficiency cascade key encryption method (CKEM) for real-time video data.

    Main Results:

    • Facial region removal showed insignificant impact on signal quality: R-value deviation < 0.06 for BVP, MAE deviation < 0.05 for HR.
    • CKEM achieved rapid encryption (5.54 × 10-5 s/frame), exceeding other methods by three orders of magnitude.
    • Encryption reduced approximate point correlation (APC) values below 0.005, indicating near-complete randomness and enhanced security.

    Conclusions:

    • SAEF effectively balances privacy protection with rPPG data integrity.
    • The framework significantly enhances real-time video encryption performance and security.
    • SAEF facilitates the development of secure, open-access rPPG datasets, promoting technological advancement.