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

Author:

Camara Carmen,Martín HonorioORCID,Peris-Lopez PedroORCID,Aldalaien MuawyaORCID

Abstract

Today, medical equipment or general-purpose devices such as smart-watches or smart-textiles can acquire a person’s vital signs. Regardless of the type of device and its purpose, they are all equipped with one or more sensors and often have wireless connectivity. Due to the transmission of sensitive data through the insecure radio channel and the need to ensure exclusive access to authorised entities, security mechanisms and cryptographic primitives must be incorporated onboard these devices. Random number generators are one such necessary cryptographic primitive. Motivated by this, we propose a True Random Number Generator (TRNG) that makes use of the GSR signal measured by a sensor on the body. After an exhaustive analysis of both the entropy source and the randomness of the output, we can conclude that the output generated by the proposed TRNG behaves as that produced by a random variable. Besides, and in comparison with the previous proposals, the performance offered is much higher than that of the earlier works.

Funder

Comunidad de Madrid

Interdisciplinary Research Funds

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Lightweight and Secure Authentication Scheme for Remote Monitoring of Patients in IoMT;IEEE Access;2024

2. Biometric Electroencephalogram Based Random Number Generator;2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC);2023-03-08

3. Using ECG signal as an entropy source for efficient generation of long random bit sequences;Journal of King Saud University - Computer and Information Sciences;2022-09

4. Design of Health Detection System for Elderly Smart Watch Based on Biosignal Acquisition;Journal of Sensors;2022-07-30

5. A High-Throughput Random Binary Sequence Generator Based on ECG;IEEE Access;2022

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