A Novel IoT Sensor Authentication Using HaLo Extraction Method and Memory Chip Variability

Abstract

In this paper, we propose flash-based hardware security primitives as a viable solution to meet the security challenges of the IoT and specifically telehealth markets. We have created a novel solution, called the High and Low (HaLo) method, that generates physical unclonable function (PUF) signatures based on process variations within flash memory in order to uniquely identify and authenticate remote sensors. The HaLo method consumes 60% 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 HaLo 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, the HaLo method could help progress the field of remote patient monitoring by accurately and efficiently authenticating remote health sensors. Keywords Physical Unclonable Function (PUF) • Internet of Things (IoT) • Flash MemoryTelecommunication in healthcare, or telehealth, provides a means by which patients can interact with medical professionals and health-related services virtually. In light of the COVID-19 worldwide pandemic, the need for secure and readily available remote patient monitoring has never been more important. Rural and low-income communities,