Peak misdetection in heart-beat-based security: Characterization and tolerance.

Area of Science:

• Biomedical Engineering
• Cybersecurity
• Signal Processing

Background:

• Inter-Pulse-Interval (IPI) from heartbeats is proposed for mobile health (mHealth) security.
• IPI-based security uses time differences between heartbeats for secure communication keys.
• The impact of imperfect heart-beat detection on IPI security is not well understood.

Purpose of the Study:

• To evaluate the security performance degradation caused by peak misdetection in IPI-based security.
• To investigate the relationship between key size and security performance with imperfect peak detection.
• To develop and assess an algorithm for mitigating the effects of misdetected peaks.

Main Methods:

• Simulated peak misdetection rates to assess security performance.
• Analyzed security drop with varying peak detection accuracy (99.9% to 99.0%).
• Evaluated authentication using different key sizes.
• Developed and tested a novel algorithm for single misdetected peak tolerance.

Main Results:

• A significant security performance drop (-70% to -303%) observed even with high peak detection rates.
• Smaller authentication keys demonstrated stronger security and potentially faster authentication with imperfect detection.
• The proposed algorithm improved security performance by up to 155% by tolerating single misdetected peaks.

Conclusions:

• Peak misdetection poses a substantial threat to IPI-based mHealth security.
• Optimizing key size and implementing robust algorithms are crucial for secure IPI-based systems.
• The developed algorithm effectively enhances security against common detection errors.