TY - GEN
T1 - Debiasing Method for Efficient Ternary Fuzzy Extractors and Ternary Physically Unclonable Functions
AU - Kazumori, Kohei
AU - Ueno, Rei
AU - Homma, Naofumi
N1 - Funding Information:
This research has been supported by JSPS KAKENHI Grants No. 19K21526. We are grateful for their support.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - 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.
AB - 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.
KW - Cryptographic key generation
KW - Debiasing
KW - Fuzzy extractor
KW - Physically unclonable function (PUF)
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U2 - 10.1109/ISMVL49045.2020.00-30
DO - 10.1109/ISMVL49045.2020.00-30
M3 - Conference contribution
AN - SCOPUS:85099784007
T3 - Proceedings of The International Symposium on Multiple-Valued Logic
SP - 52
EP - 57
BT - Proceedings - 2020 IEEE 50th International Symposium on Multiple-Valued Logic, ISMVL 2020
PB - IEEE Computer Society
T2 - 50th IEEE International Symposium on Multiple-Valued Logic, ISMVL 2020
Y2 - 9 November 2020 through 11 November 2020
ER -