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).