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February 12, 2026ACM Transactions on Computation Theory0 citationsOpen Access

Kolmogorov Complexity Characterizes Statistical Zero Knowledge

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EAEric AllenderSHShuichi HiraharaHTHarsha Tirumala

Key Points

  • The research aims to establish the conditions under which a promise problem has a non-interactive statistical zero-knowledge proof system.
  • Analyzed the relationship between promise problems and Kolmogorov-random strings.
  • Developed a framework for random reduction through polynomial-time techniques.
  • Extended existing work on zero-knowledge proof systems.
  • Identified that a promise problem has non-interactive statistical zero-knowledge proofs if reduced to Kolmogorov-random strings.
  • Showed that this reduction includes a superlogarithmic additive approximation term.
  • Provided new characterizations related to the complexity classes SZK, NISZK, and SZK L.

Abstract

We show that a decidable promise problem has a non-interactive statistical zero-knowledge proof system if and only if it is randomly reducible via an honest polynomial-time reduction to a promise problem for Kolmogorov-random strings, with a superlogarithmic additive approximation term. This extends work by Saks and Santhanam (CCC 2022). (Saks and Santhanam showed that promise problems that can be reduced in this way to such an approximation of the Kolmogorov-random strings have (possibly interactive) zero-knowledge proof systems, and they did not address the converse implication.) We build on this to give new characterizations of Statistical Zero Knowledge SZK , as well as the related classes NISZK L and SZK L .

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Cite This Study

Allender et al. (2026) studied this question.

synapsesocial.com/papers/698d6dc15be6419ac0d52ecfhttps://doi.org/10.1145/3795688
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