Security primitive design with nanoscale devices: A case study with resistive RAM

Robert Karam, Rui Liu, Pai Yu Chen, Shimeng Yu, Swarup Bhunia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Inherent stochastic physical mechanisms in emerging nonvolatile memories (NVMs), such as resistive random-access-memory (RRAM), have recently been explored for hardware security applications. Unlike the conventional silicon Physical Unclonable Functions (PUFs) that are solely based on manufacturing process variation, RRAM has some intrinsic randomness in its physical mechanisms that can be utilized as entropy sources; for instance, resistance variation, random telegraph noise, and probabilistic switching behaviors. This paper reviews the challenges and opportunities in building security primitives with emerging devices. In particular, it presents research progress of RRAM-based hardware security primitives, including PUF and True Random Number Generator (TRNG).

Original languageEnglish (US)
Title of host publicationGLSVLSI 2016 - Proceedings of the 2016 ACM Great Lakes Symposium on VLSI
PublisherAssociation for Computing Machinery
Pages299-304
Number of pages6
Volume18-20-May-2016
ISBN (Electronic)9781450342742
DOIs
StatePublished - May 18 2016
Event26th ACM Great Lakes Symposium on VLSI, GLSVLSI 2016 - Boston, United States
Duration: May 18 2016May 20 2016

Other

Other26th ACM Great Lakes Symposium on VLSI, GLSVLSI 2016
CountryUnited States
CityBoston
Period5/18/165/20/16

Keywords

  • Hardware security
  • PUF
  • Resistance variation
  • RRAM
  • Security of nanoscale devices
  • Switching probability
  • TRNG

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Karam, R., Liu, R., Chen, P. Y., Yu, S., & Bhunia, S. (2016). Security primitive design with nanoscale devices: A case study with resistive RAM. In GLSVLSI 2016 - Proceedings of the 2016 ACM Great Lakes Symposium on VLSI (Vol. 18-20-May-2016, pp. 299-304). Association for Computing Machinery. https://doi.org/10.1145/2902961.2903042