Debiasing Method for Efficient Ternary Fuzzy Extractors and Ternary Physically Unclonable Functions

Kohei Kazumori, Rei Ueno, Naofumi Homma

研究成果: Conference contribution

抄録

In this paper, we propose a debiasing method for efficiently extracting unbiased ternary strings from biased ternary physically unclonable functions (PUFs). The conventional debiasing method applicable to ternary PUFs extracts unbiased strings from ternary PUFs by discarding the response of certain cells according to the ternary-extended von Neumann corrector (VNC). The proposed method probabilistically extracts the information, which is discarded in the conventional method, as the third value based on a rejection sampling. To demonstrate the effectiveness and efficiency of the proposed method, we evaluate the PUF sizes required for reliable 128-bit cryptographic key generation from PUFs with varying biases and error rates. The results show that the proposed method can reduce the PUF size by 63%, compared with the conventional method.

本文言語English
ホスト出版物のタイトルProceedings - 2020 IEEE 50th International Symposium on Multiple-Valued Logic, ISMVL 2020
出版社IEEE Computer Society
ページ52-57
ページ数6
ISBN(電子版)9781728154060
DOI
出版ステータスPublished - 2020 11
イベント50th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2020 - Miyazaki, Japan
継続期間: 2020 11 92020 11 11

出版物シリーズ

名前Proceedings of The International Symposium on Multiple-Valued Logic
2020-November
ISSN(印刷版)0195-623X

Conference

Conference50th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2020
国/地域Japan
CityMiyazaki
Period20/11/920/11/11

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 数学 (全般)

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