# Constructing practical Fuzzy Extractors using QIM

I.R. Buhan, J.M. Doumen, Pieter H. Hartel, Raymond N.J. Veldhuis

Research output: Book/ReportReportProfessional

### Abstract

Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers $( \frac{log_2 6}{2}-1 ) \approx 0.3$ extra bits per dimension of the space compared to the known square quantization based fuzzy extractor.
Original language Undefined Enschede Distributed and Embedded Security (DIES) 15 Published - Jul 2007

### Publication series

Name CTIT Technical Report Series University of Twente, CTIT LNCS4549/TR-CTIT-07-52 1381-3625

### Keywords

• EWI-10785
• SCS-Cybersecurity
• IR-59974
• METIS-241791
• SCS-Safety

### Cite this

Buhan, I. R., Doumen, J. M., Hartel, P. H., & Veldhuis, R. N. J. (2007). Constructing practical Fuzzy Extractors using QIM. (CTIT Technical Report Series; No. LNCS4549/TR-CTIT-07-52). Enschede: Distributed and Embedded Security (DIES).
Buhan, I.R. ; Doumen, J.M. ; Hartel, Pieter H. ; Veldhuis, Raymond N.J. / Constructing practical Fuzzy Extractors using QIM. Enschede : Distributed and Embedded Security (DIES), 2007. 15 p. (CTIT Technical Report Series; LNCS4549/TR-CTIT-07-52).
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abstract = "Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers $( \frac{log_2 6}{2}-1 ) \approx 0.3$ extra bits per dimension of the space compared to the known square quantization based fuzzy extractor.",
keywords = "EWI-10785, SCS-Cybersecurity, IR-59974, METIS-241791, SCS-Safety",
author = "I.R. Buhan and J.M. Doumen and Hartel, {Pieter H.} and Veldhuis, {Raymond N.J.}",
year = "2007",
month = "7",
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series = "CTIT Technical Report Series",
publisher = "Distributed and Embedded Security (DIES)",
number = "LNCS4549/TR-CTIT-07-52",

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Buhan, IR, Doumen, JM, Hartel, PH & Veldhuis, RNJ 2007, Constructing practical Fuzzy Extractors using QIM. CTIT Technical Report Series, no. LNCS4549/TR-CTIT-07-52, Distributed and Embedded Security (DIES), Enschede.

Constructing practical Fuzzy Extractors using QIM. / Buhan, I.R.; Doumen, J.M.; Hartel, Pieter H.; Veldhuis, Raymond N.J.

Enschede : Distributed and Embedded Security (DIES), 2007. 15 p. (CTIT Technical Report Series; No. LNCS4549/TR-CTIT-07-52).

Research output: Book/ReportReportProfessional

TY - BOOK

T1 - Constructing practical Fuzzy Extractors using QIM

AU - Buhan, I.R.

AU - Doumen, J.M.

AU - Hartel, Pieter H.

AU - Veldhuis, Raymond N.J.

PY - 2007/7

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N2 - Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers $( \frac{log_2 6}{2}-1 ) \approx 0.3$ extra bits per dimension of the space compared to the known square quantization based fuzzy extractor.

AB - Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers $( \frac{log_2 6}{2}-1 ) \approx 0.3$ extra bits per dimension of the space compared to the known square quantization based fuzzy extractor.

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KW - IR-59974

KW - METIS-241791

KW - SCS-Safety

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BT - Constructing practical Fuzzy Extractors using QIM

PB - Distributed and Embedded Security (DIES)

CY - Enschede

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Buhan IR, Doumen JM, Hartel PH, Veldhuis RNJ. Constructing practical Fuzzy Extractors using QIM. Enschede: Distributed and Embedded Security (DIES), 2007. 15 p. (CTIT Technical Report Series; LNCS4549/TR-CTIT-07-52).