Publication

Key Extraction From General Nondiscrete Signals

Verbitskiy, E. A., Tuyls, P., Obi, C., Schoenmakers, B. & Škorić, B., Jun-2010, In : IEEE transactions on information forensics and security. 5, 2, p. 269-279 11 p.

Research output: Contribution to journalArticleAcademic

APA

Verbitskiy, E. A., Tuyls, P., Obi, C., Schoenmakers, B., & Škorić, B. (2010). Key Extraction From General Nondiscrete Signals. IEEE transactions on information forensics and security, 5(2), 269-279. https://doi.org/10.1109/TIFS.2010.2046965

Author

Verbitskiy, Evgeny A. ; Tuyls, Pim ; Obi, Chibuzo ; Schoenmakers, Berry ; Škorić, Boris. / Key Extraction From General Nondiscrete Signals. In: IEEE transactions on information forensics and security. 2010 ; Vol. 5, No. 2. pp. 269-279.

Harvard

Verbitskiy, EA, Tuyls, P, Obi, C, Schoenmakers, B & Škorić, B 2010, 'Key Extraction From General Nondiscrete Signals', IEEE transactions on information forensics and security, vol. 5, no. 2, pp. 269-279. https://doi.org/10.1109/TIFS.2010.2046965

Standard

Key Extraction From General Nondiscrete Signals. / Verbitskiy, Evgeny A.; Tuyls, Pim; Obi, Chibuzo; Schoenmakers, Berry; Škorić, Boris.

In: IEEE transactions on information forensics and security, Vol. 5, No. 2, 06.2010, p. 269-279.

Research output: Contribution to journalArticleAcademic

Vancouver

Verbitskiy EA, Tuyls P, Obi C, Schoenmakers B, Škorić B. Key Extraction From General Nondiscrete Signals. IEEE transactions on information forensics and security. 2010 Jun;5(2):269-279. https://doi.org/10.1109/TIFS.2010.2046965


BibTeX

@article{9c7ae1aefd3a4406aed28dc8fc41034a,
title = "Key Extraction From General Nondiscrete Signals",
abstract = "We address the problem of designing optimal schemes for the generation of secure cryptographic keys from continuous noisy data. We argue that, contrary to the discrete case, a universal fuzzy extractor does not exist. This implies that in the continuous case, key extraction schemes have to be designed for particular probability distributions. We extend the known definitions of the correctness and security properties of fuzzy extractors. Our definitions apply to continuous as well as discrete variables. We propose a generic construction for fuzzy extractors from noisy continuous sources, using independent partitions. The extra freedom in the choice of discretization, which does not exist in the discrete case, is advantageously used to give the extracted key a uniform distribution. We analyze the privacy properties of the scheme and the error probabilities in a one-dimensional toy model with simplified noise. Finally, we study the security implications of incomplete knowledge of the source’s probability distribution P. We derive a bound on the min-entropy of the extracted key under the worst-case assumption, where the attacker knows P exactly.",
keywords = "privacy, fuzzy extractors, biometrics",
author = "Verbitskiy, {Evgeny A.} and Pim Tuyls and Chibuzo Obi and Berry Schoenmakers and Boris Škorić",
note = "Relation: https://www.rug.nl/informatica/onderzoek/bernoulli Rights: University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science",
year = "2010",
month = "6",
doi = "10.1109/TIFS.2010.2046965",
language = "English",
volume = "5",
pages = "269--279",
journal = "IEEE transactions on information forensics and security",
issn = "1556-6013",
number = "2",

}

RIS

TY - JOUR

T1 - Key Extraction From General Nondiscrete Signals

AU - Verbitskiy, Evgeny A.

AU - Tuyls, Pim

AU - Obi, Chibuzo

AU - Schoenmakers, Berry

AU - Škorić, Boris

N1 - Relation: https://www.rug.nl/informatica/onderzoek/bernoulli Rights: University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science

PY - 2010/6

Y1 - 2010/6

N2 - We address the problem of designing optimal schemes for the generation of secure cryptographic keys from continuous noisy data. We argue that, contrary to the discrete case, a universal fuzzy extractor does not exist. This implies that in the continuous case, key extraction schemes have to be designed for particular probability distributions. We extend the known definitions of the correctness and security properties of fuzzy extractors. Our definitions apply to continuous as well as discrete variables. We propose a generic construction for fuzzy extractors from noisy continuous sources, using independent partitions. The extra freedom in the choice of discretization, which does not exist in the discrete case, is advantageously used to give the extracted key a uniform distribution. We analyze the privacy properties of the scheme and the error probabilities in a one-dimensional toy model with simplified noise. Finally, we study the security implications of incomplete knowledge of the source’s probability distribution P. We derive a bound on the min-entropy of the extracted key under the worst-case assumption, where the attacker knows P exactly.

AB - We address the problem of designing optimal schemes for the generation of secure cryptographic keys from continuous noisy data. We argue that, contrary to the discrete case, a universal fuzzy extractor does not exist. This implies that in the continuous case, key extraction schemes have to be designed for particular probability distributions. We extend the known definitions of the correctness and security properties of fuzzy extractors. Our definitions apply to continuous as well as discrete variables. We propose a generic construction for fuzzy extractors from noisy continuous sources, using independent partitions. The extra freedom in the choice of discretization, which does not exist in the discrete case, is advantageously used to give the extracted key a uniform distribution. We analyze the privacy properties of the scheme and the error probabilities in a one-dimensional toy model with simplified noise. Finally, we study the security implications of incomplete knowledge of the source’s probability distribution P. We derive a bound on the min-entropy of the extracted key under the worst-case assumption, where the attacker knows P exactly.

KW - privacy

KW - fuzzy extractors

KW - biometrics

U2 - 10.1109/TIFS.2010.2046965

DO - 10.1109/TIFS.2010.2046965

M3 - Article

VL - 5

SP - 269

EP - 279

JO - IEEE transactions on information forensics and security

JF - IEEE transactions on information forensics and security

SN - 1556-6013

IS - 2

ER -

ID: 14403652