English

Computationally Data-Independent Memory Hard Functions

Cryptography and Security 2019-11-18 v1 Data Structures and Algorithms

Abstract

Memory hard functions (MHFs) are an important cryptographic primitive that are used to design egalitarian proofs of work and in the construction of moderately expensive key-derivation functions resistant to brute-force attacks. Broadly speaking, MHFs can be divided into two categories: data-dependent memory hard functions (dMHFs) and data-independent memory hard functions (iMHFs). iMHFs are resistant to certain side-channel attacks as the memory access pattern induced by the honest evaluation algorithm is independent of the potentially sensitive input e.g., password. While dMHFs are potentially vulnerable to side-channel attacks (the induced memory access pattern might leak useful information to a brute-force attacker), they can achieve higher cumulative memory complexity (CMC) in comparison than an iMHF. In this paper, we introduce the notion of computationally data-independent memory hard functions (ciMHFs). Intuitively, we require that memory access pattern induced by the (randomized) ciMHF evaluation algorithm appears to be independent from the standpoint of a computationally bounded eavesdropping attacker --- even if the attacker selects the initial input. We then ask whether it is possible to circumvent known upper bound for iMHFs and build a ciMHF with CMC Ω(N2)\Omega(N^2). Surprisingly, we answer the question in the affirmative when the ciMHF evaluation algorithm is executed on a two-tiered memory architecture (RAM/Cache). See paper for the full abstract.

Keywords

Cite

@article{arxiv.1911.06790,
  title  = {Computationally Data-Independent Memory Hard Functions},
  author = {Mohammad Hassan Ameri and Jeremiah Blocki and Samson Zhou},
  journal= {arXiv preprint arXiv:1911.06790},
  year   = {2019}
}

Comments

To appear at ITCS 2020

R2 v1 2026-06-23T12:17:25.929Z