Physical Unclonable Function-Based Key Sharing via Machine Learning for IoT Security

Jiliang Zhang

doi:10.1109/TIE.2019.2938462

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Physical Unclonable Function-Based Key Sharing via Machine Learning for IoT Security

2020-08-01

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Jiliang Zhang *

曲

曲刚 (Gang Qu)

DOI：10.1109/TIE.2019.2938462

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Abstract

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In many industry Internet of Things applications, resources like CPU, memory, and battery power are limited and cannot afford the classic cryptographic security solutions. Silicon physical unclonable function (PUF) is a lightweight security primitive that exploits manufacturing variations during the chip fabrication process for key generation and/or device authentication. However, traditional weak PUFs such as ring oscillator (RO) PUF generate chip-unique key for each device, which restricts their application in security protocols where the same key is required to be shared in resource-constrained devices. In this article, in order to address this issue, we propose a PUF-based key sharing method for the first time. The basic idea is to implement one-to-one input-output mapping with lookup table (LUT)-based interstage crossing structures in each level of inverters of RO PUF. Individual customization on configuration bits of interstage crossing structure and different RO selections with challenges bring high flexibility. Therefore, with the flexible configuration of interstage crossing structures and challenges, crossover RO PUF can generate the same shared key for resource-constrained devices, which enables a new application for lightweight key sharing protocols.

Keywords:

Key-sharing

machine learning (ML)

physical unclonable function (PUF)