Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features

Area of Science:

• Biometrics and Security
• Wearable Technology
• Signal Processing

Background:

• Growing popularity of wearable devices necessitates robust data security solutions.
• Bio-crypto keys (bio-keys) offer next-generation security but face implementation challenges.
• Electrocardiograms (ECGs) are a promising biometric for bio-keys, yet intra-individual variability is a hurdle.

Purpose of the Study:

• To evaluate the feasibility of a stable, flexible, and convenient bio-key system using ECGs.
• To develop a method for minimizing biosignal variability in ECGs for secure authentication.
• To optimize parameter combinations for effective bio-key generation.

Main Methods:

• ECG signal normalization to reduce variability.
• Clustering-based binarization for signal processing.
• Fuzzy extractor implementation for personalized seed generation.
• Evaluation of various parameter combinations for bio-key generation.

Main Results:

• Achieved a maximum entropy of 0.99, indicating high randomness and security.
• Demonstrated an authentication accuracy of 95% for personal identification.
• Identified optimal parameter combinations for effective bio-key generation.

Conclusions:

• The proposed ECG-based bio-key system offers a stable, flexible, and convenient solution for wearable device security.
• This approach effectively minimizes biosignal variability, enhancing the reliability of bio-keys.
• The research presents potential advancements for security technologies in wearable devices and healthcare systems.