A precise non-asymptotic complexity analysis of parallel hash functions without tree topology constraints

• Published in: Journal of parallel and distributed computing Vol. 137; pp. 246 - 251
• Main Author: Atighehchi, Kevin
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.03.2020; Elsevier
• Subjects: Computer Science; Hash functions; Merkle trees; Parallel algorithms; Prefix-free Merkle–Damgård; Sponge functions; Hash functions; Merkle trees; Prefix-free Merkle–Damgård; Sponge functions; Parallel algorithms
• ISSN: 0743-7315; 1096-0848
• DOI: 10.1016/j.jpdc.2019.10.002

A recent work shows how we can optimize a tree based mode of operation for a hash function where the sizes of input message blocks and digest are the same, subject to the constraint that the involved tree structure has all its leaves at the same depth. In this work, we show that we can further optimize the running time of such a mode by using a tree having leaves at all its levels. We make the assumption that the input message block has a size a multiple of that of the digest and denote by d the ratio block size over digest size. The running time is evaluated in terms of number of operations performed by the hash function, i.e. the number of calls to its underlying function. It turns out that a digest can be computed in ⌈logd+1(l∕2)⌉+2 evaluations of the underlying function using ⌈l∕2⌉ processors, where l is the number of blocks of the message. Other results of interest are discussed, such as the optimization of the parallel running time for a tree of restricted height. •Estimation of the optimal parallel time obtained using hash trees of smallest height.•In particular, both the running time and the number of involved processors are optimized.•Estimation of the optimal parallel time for hash trees of unrestricted height.•Optimization of the number of involved processors without changing this running time.•Complexity results about the optimal parallel time for a restricted number of processors.•All the proposed tree-based modes support live-streaming for a restricted number of processors.