Cryptology ePrint Archive: Report 2021/1067

A Tale of Twin Primitives: Single-chip Solution for PUFs and TRNGs

Kuheli Pratihar and Urbi Chatterjee and Manaar Alam and Debdeep Mukhopadhyay and Rajat Subhra Chakraborty

Abstract: Physically Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) are two highly useful hardware primitives to build up the root-of-trust for an embedded device. PUFs are designed to offer repetitive and instance-specific randomness, whereas TRNGs are expected to be invariably random. In this paper, we present a dual-mode PUF-TRNG design that utilises two different hardware-intrinsic properties, i.e. oscillation frequency of the Transition Effect Ring Oscillator (TERO) cell and the propagation delay of a buffer within the cell to serve the purpose of both PUF and TRNG depending on the exact requirement of the application. The PUF design is also proposed to have a built-in resistance to machine learning (ML) and deep learning (DL) attacks, whereas the TRNG exhibits sufficient randomness.

Category / Keywords: implementation / True Random Number Generators · Physically Unclonable Functions · Transient Effect Ring Oscillator · Feedback · Recurrent Neural Network · Internet of Things (IoT) · PUF modelling

Date: received 17 Aug 2021, last revised 25 Dec 2021

Contact author: its kuheli96 at gmail com, urbi ism at gmail com, alam manaar at gmail com, debdeep mukhopadhyay at gmail com, rschakraborty at gmail com

Available format(s): PDF | BibTeX Citation

Note: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

Version: 20211225:150825 (All versions of this report)

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