Statistical Modeling of SRAM PUF Cell Mismatch Shift Distribution after Hot Carrier Injection Burn-In

Kunyang Liu, Kiyoshi Takeuchi, Hirofumi Shinohara

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

Abstract

This article presents statistical modeling for bitcell mismatch shift with respect to hot carrier injection (HCI) burn-in on a static random access memory (SRAM)-based physically unclonable function (PUF). A compound distribution based on a Poisson distribution and a Gamma distribution is used to model the mismatch shift. The Poisson distribution models the number of injected hot carriers, and the Gamma distribution models the mismatch shift value induced by a certain number of injected hot carriers. This model is evaluated by testing chips fabricated in a 130-nm CMOS process. Experimental results collected from 2-min to 8-min HCI burn-in match the model well. Results also show that the number of injected hot carriers has a linear relation with the burn-in time to the power 0.6.

Original languageEnglish
Title of host publication2022 IEEE 34th International Conference on Microelectronic Test Structures, ICMTS 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665485661
DOIs
Publication statusPublished - 2022
Event34th IEEE International Conference on Microelectronic Test Structures, ICMTS 2022 - Cleveland, United States
Duration: 2022 Mar 212022 Apr 15

Publication series

NameIEEE International Conference on Microelectronic Test Structures
Volume2022-March

Conference

Conference34th IEEE International Conference on Microelectronic Test Structures, ICMTS 2022
Country/TerritoryUnited States
CityCleveland
Period22/3/2122/4/15

Keywords

  • Gamma distribution
  • hot carrier injection (HCI)
  • model
  • physically unclonable function (PUF)
  • Poisson distribution
  • static random access memory (SRAM)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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