### Abstract

Original language | Undefined |
---|---|

Place of Publication | Enschede |

Publisher | Distributed and Embedded Security (DIES) |

Number of pages | 15 |

Publication status | Published - Jul 2007 |

### Publication series

Name | CTIT Technical Report Series |
---|---|

Publisher | University of Twente, CTIT |

No. | LNCS4549/TR-CTIT-07-52 |

ISSN (Print) | 1381-3625 |

### Keywords

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

### Cite this

*Constructing practical Fuzzy Extractors using QIM*. (CTIT Technical Report Series; No. LNCS4549/TR-CTIT-07-52). Enschede: Distributed and Embedded Security (DIES).

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*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.

Research output: Book/Report › Report › Professional

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

Y1 - 2007/7

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.

KW - EWI-10785

KW - SCS-Cybersecurity

KW - IR-59974

KW - METIS-241791

KW - SCS-Safety

M3 - Report

T3 - CTIT Technical Report Series

BT - Constructing practical Fuzzy Extractors using QIM

PB - Distributed and Embedded Security (DIES)

CY - Enschede

ER -