Compactness of Hashing Modes and Efficiency beyond Merkle Tree

TL;DR

This paper introduces a new compactness efficiency notion for hash functions, proposes two tree-based modes of operation, and demonstrates their optimal collision resistance and indifferentiability properties beyond Merkle trees.

Contribution

It presents the ABR and ABR+ modes of operation, achieving optimal efficiency and security properties for larger domain hash functions, extending beyond Merkle tree limitations.

Findings

ABR mode is optimally compact with asymptotic collision resistance.

ABR+ mode achieves indifferentiability up to 2^{n/2-ε} queries.

Both modes process additional data blocks compared to Merkle trees.

Abstract

We revisit the classical problem of designing optimally efficient cryptographically secure hash functions. Hash functions are traditionally designed via applying modes of operation on primitives with smaller domains. The results of Shrimpton and Stam (ICALP 2008), Rogaway and Steinberger (CRYPTO 2008), and Mennink and Preneel (CRYPTO 2012) show how to achieve optimally efficient designs of $2n$-to-$n$-bit compression functions from non-compressing primitives with asymptotically optimal $2^{n/2-\epsilon}$-query collision resistance. Designing optimally efficient and secure hash functions for larger domains ($> 2n$ bits) is still an open problem. In this work we propose the new \textit{compactness} efficiency notion. It allows us to focus on asymptotically optimally collision resistant hash function and normalize their parameters based on Stam's bound from CRYPTO 2008 to obtain maximal efficiency. We then present two tree-based modes of operation -Our first construction is an \underline{A}ugmented \underline{B}inary T\underline{r}ee (ABR) mode. The design is a $(2^{\ell}+2^{\ell-1} -1)n$-to-$n$-bit hash function making a total of $(2^{\ell}-1)$ calls to $2n$-to-$n$-bit compression functions for any $\ell\geq 2$. Our construction is optimally compact with asymptotically (optimal) $2^{n/2-\epsilon}$-query collision resistance in the ideal model. For a tree of height $\ell$, in comparison with Merkle tree, the $ABR$ mode processes additional $(2^{\ell-1}-1)$ data blocks making the same number of internal compression function calls. -While the $ABR$ mode achieves collision resistance, it fails to achieve indifferentiability from a random oracle within $2^{n/3}$ queries. $ABR^{+}$ compresses only $1$ less data block than $ABR$ with the same number of compression calls and achieves in addition indifferentiability up to $2^{n/2-\epsilon}$ queries.