Self-masking for hardening inversions

Paweł Cyprys, Shlomi Dolev, Shlomo Moran

Research output: Contribution to journalArticlepeer-review

Abstract

The question of whether one-way functions (i.e., functions that are easy to compute but hard to invert) exist is arguably one of the central problems in complexity theory, both from theoretical and practical aspects. While proving that such functions exist could be hard, there were quite a few attempts to provide functions that are one way “in practice”, namely, they are easy to compute, but there are no known polynomial time algorithms that compute their (generalized) inverse (or that computing their inverse is as hard as notoriously difficult tasks, like factoring very large integers). In this paper, we introduce the self-masking technique, which converts polynomial time computable functions to functions that are likely to be harder to invert. The technique is first defined for univalent functions (note that one way functions that are univalent are basic ingredients for cryptographic protocols). Informally, a self masked version of a univalent function f, denoted [f], replaces two masking substrings of f(x) by their XOR. The masking substrings are critical if [f] remains univalent (w.h.p.). Thus, when the masking substrings are critical, inverting [f](x) is at least as hard as reconstructing the masking substrings from their XOR. We apply this technique to functions based on variants of the subset sum problem and obtain functions that resist known techniques for inverting the original, unmasked functions (see, e.g., [13]). Applications of this technique to other functions, as well as its extension to multivalent functions, are also discussed.

Original languageEnglish
Article number115094
JournalTheoretical Computer Science
Volume1032
DOIs
StatePublished - 29 Mar 2025

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Self-masking for hardening inversions'. Together they form a unique fingerprint.

Cite this