Date of Award

Spring 2021

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2021.

Department

Electrical and Computer Engineering

First Advisor

Sara Tehranipoor

Abstract

In light of the COVID-19 world-wide pandemic, the need for secure and readily available remote patient monitoring has never been more important. Rural and low income communities in particular have been severely impacted by the lack of accessibility to in-person healthcare. This has created the need for access to remote patient monitoring and virtual health visits in order for greater accessibility to premier care. In this paper, we propose hardware security primitives as a viable solution to meet the security challenges of the telehealth market. We have created a novel solution, called the High-Low (HiLo) method, that generates physical unclonable function (PUF) signatures based on process variation within flash memory in order to uniquely identify and authenticate remote sensors. The HiLo method consumes 20x less power than conventional authentication schemes, has an average latency of only 39ms for signature generation, and can be readily implemented through firmware on ONFI 2.2 compliant off-the-shelf NAND flash memory chips. The HiLo method generates 512 bit signatures with an average error rate of 5.9 * 10-4, while also adapting for flash chip aging. Due to its low latency, low error rate, and high power efficiency, we believe that the HiLo method could help progress the field of remote patient monitoring by accurately and efficiently authenticating remote health sensors.

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