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SQAHO-IoMT: A Post-Quantum Secure and AI-Resilient Aggregation Framework for Smart Healthcare Systems.

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    We developed SQAHO-IoMT, a security framework for the Internet of Medical Things (IoMT). It uses post-quantum encryption and AI-aware obfuscation to protect patient data from cyber threats, ensuring secure smart healthcare.

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    Area of Science:

    • Cybersecurity
    • Medical Technology
    • Applied Cryptography

    Background:

    • The Internet of Medical Things (IoMT) enables precision medicine but faces security risks from advanced threats like AI and quantum computing.
    • Protecting sensitive patient data and device integrity in complex IoMT ecosystems is a significant challenge.
    • Existing security measures may not adequately address emerging threats, necessitating novel solutions.

    Purpose of the Study:

    • To propose SQAHO-IoMT, a unified security framework for resource-constrained medical devices in IoMT.
    • To enhance data aggregation security and privacy in smart healthcare systems.
    • To provide robust protection against both conventional and emerging cyber threats, including quantum and AI-driven attacks.

    Main Methods:

    • Implementation of Ring-LWE based post-quantum encryption with hierarchical keys for privacy-preserving data aggregation.
    • Introduction of noise-flooded obfuscation to counter AI-based reverse engineering of aggregation logic and device behavior.
    • Utilizing a threshold-based key-sharing mechanism for enhanced compromise tolerance and decentralized resilience.

    Main Results:

    • Formal security analysis confirms 100-bit quantum resistance against key recovery and logic extraction.
    • Achieved 128-bit post-quantum integrity through optimized digital signatures.
    • Demonstrated low latency (81.1 ms) and minimal energy consumption (0.13 mJ) on a 32-bit ARM Cortex-M4 for 100-node deployments.

    Conclusions:

    • SQAHO-IoMT effectively combines post-quantum cryptography with AI-aware obfuscation for secure and trustworthy data aggregation in smart healthcare.
    • The framework enhances the reliability of analytics for personalized treatment, critical care monitoring, and remote patient management.
    • SQAHO-IoMT represents a significant advancement in securing IoMT ecosystems against sophisticated cyber threats.