Bandwidth-Hard Functions: Reductions and Lower Bounds

Jeremiah Blocki, Peiyuan Liu, Ling Ren, Samson Zhou

Research output: Contribution to journalArticlepeer-review

Abstract

Memory Hard Functions (MHFs) have been proposed as an answer to the growing inequality between the computational speed of general purpose CPUs and ASICs. MHFs have seen widespread applications including password hashing, key stretching and proofs of work. Several metrics have been proposed to quantify the memory hardness of a function. Cumulative memory complexity (CMC) quantifies the cost to acquire/build the hardware to evaluate the function repeatedly at a given rate. By contrast, bandwidth hardness quantifies the energy costs of evaluating this function. Ideally, a good MHF would be both bandwidth hard and have high CMC. While the CMC of leading MHF candidates is well understood, little is known about the bandwidth hardness of many prominent MHF candidates. Our contributions are as follows: First, we provide the first reduction proving that, in the parallel random oracle model (pROM), the bandwidth hardness of a data-independent MHF (iMHF) is described by the red-blue pebbling cost of the directed acyclic graph associated with that iMHF. Second, we show that the goals of designing an MHF with high CMC/bandwidth hardness are well aligned. Any function (data-independent or not) with high CMC also has relatively high bandwidth costs. Third, we prove that in the pROM the prominent iMHF candidates such as Argon2i, aATSample and DRSample are maximally bandwidth hard. Fourth, we prove the first unconditional tight lower bound on the bandwidth hardness of a prominent data-dependent MHF called Scrypt in the pROM. Finally, we show the problem of finding the minimum cost red–blue pebbling of a directed acyclic graph is NP-hard.

Original languageEnglish (US)
Article number16
JournalJournal of Cryptology
Volume37
Issue number2
DOIs
StatePublished - Apr 2024

Keywords

  • Bandwidth hardness
  • Cumulative memory complexity
  • Energy cost
  • Graph pebbling
  • Memory-hard functions
  • Parallel random oracle model

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Applied Mathematics

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