Design and Analysis of a True Random Number Generator Based on GSR Signals for Body Sensor Networks.

Area of Science:

• Biomedical Engineering
• Cybersecurity
• Signal Processing

Background:

• Wearable devices and smart textiles collect vital signs using sensors and wireless connectivity.
• Secure transmission of sensitive data requires onboard cryptographic primitives like random number generators.
• Existing solutions may lack sufficient performance or robust security for these applications.

Purpose of the Study:

• To propose and validate a novel True Random Number Generator (TRNG) for wearable devices.
• To leverage the Galvanic Skin Response (GSR) signal as an entropy source for TRNG.
• To enhance the security of sensitive data transmission from body-worn sensors.

Main Methods:

• Development of a TRNG utilizing the GSR signal measured by an on-body sensor.
• Exhaustive analysis of the entropy source (GSR signal) for randomness.
• Performance evaluation and comparison with existing TRNG methods.

Main Results:

• The proposed TRNG successfully generates random numbers with statistical properties comparable to a true random variable.
• The GSR signal is confirmed as a viable and effective entropy source.
• The TRNG demonstrates significantly higher performance compared to previous proposals.

Conclusions:

• The GSR-based TRNG is a secure and high-performance solution for wearable devices.
• This approach enhances the security of sensitive physiological data.
• The findings pave the way for more secure and efficient connected health technologies.