G-PUF: An Intrinsic PUF Based on GPU Error Signatures

Bruno Forlin, Ronaldo Husemann, Luigi Carro, Cezar Reinbrecht, Said Hamdioui, Mottaqiallah Taouil

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Physically Unclonable Functions (PUFs) are security primitives that provide trustworthy hardware for key-generation and device authentication. Among them, in contrast to dedicated PUFs, intrinsic PUFs are created from existing hardware components that exploit their variability through software. In this work we focus on GPUs and present G-PUF, a PUF implemented entirely in software on CUDA and hence does not require hardware modifications. Our results show that G-PUF has comparable characteristics to SRAM and DRAM PUFs in terms of uniformity 55.61% and reliability 90.09%.

Original languageEnglish
Title of host publication2020 IEEE European Test Symposium (ETS)
Subtitle of host publicationProceedings
PublisherIEEE
Pages1-2
Number of pages2
ISBN (Electronic)978-1-7281-4312-5
ISBN (Print)978-1-7281-4313-2
DOIs
Publication statusPublished - 2020
EventETS 2020: 2020 IEEE European Test Symposium - Tallinn, Estonia
Duration: 25 May 202029 May 2020

Conference

ConferenceETS 2020
CountryEstonia
CityTallinn
Period25/05/2029/05/20

Keywords

  • G-PUF
  • GPU
  • Intrinsic PUF
  • Physically Unclonable Functions
  • Security

Fingerprint Dive into the research topics of 'G-PUF: An Intrinsic PUF Based on GPU Error Signatures'. Together they form a unique fingerprint.

Cite this