Constructing practical Fuzzy Extractors using QIM

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

    Research output: Book/ReportReportProfessional

    46 Downloads (Pure)

    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 languageUndefined
    Place of PublicationEnschede
    PublisherDistributed and Embedded Security (DIES)
    Number of pages15
    Publication statusPublished - Jul 2007

    Publication series

    NameCTIT Technical Report Series
    PublisherUniversity 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

    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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    keywords = "EWI-10785, SCS-Cybersecurity, IR-59974, METIS-241791, SCS-Safety",
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    year = "2007",
    month = "7",
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    series = "CTIT Technical Report Series",
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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

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    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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    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).