Cryptology ePrint Archive: Report 2018/701

Information-Theoretic Secure Sketch for Noisy Sources of Low Entropy

Yen-Lung Lai and Zhe Jin

Abstract: Secure sketch produces public information of its input $w$ without revealing it, yet, allows the exact recovery of $w$ given another value $w'$ that is close to $w$. Therefore, it can be used to reliably reproduce any error-prone secret sources (i.e., biometric) stored in secret storage. However, some sources have lower entropy compared to the error itself, formally called ``more error than entropy", a standard secure sketch cannot show its security promise perfectly to these kinds of sources. Besides, when same input is reused for multiple sketches generation, the complex error process of the input further results to security uncertainty, and offer no security guarantee. This paper focuses on secure sketch. We propose a new technique to generate re-usable secure sketch. We show security to low entropy sources and enable error correction up to Shannon bound via unique decoding. Our security defined information theoretically with Shannon entropy over some worst case random error distribution adding to the input source. In particular, given a sketch of size $n$, our new technique is capable of providing security guarantee (minimum of single bit) for all input distributions with min-entropy at least ${\log(n+1)}+1$.

Category / Keywords: applications / Secure Sketch, Error Correction, Information Theory, Fuzzy Extractor

Date: received 24 Jul 2018, last revised 24 May 2019

Contact author: yenlung lai at monash edu

Available format(s): PDF | BibTeX Citation

Version: 20190525:033325 (All versions of this report)

Short URL: ia.cr/2018/701


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