Statistical randomized encodings: A complexity theoretic view

Shweta Agrawal, Yuval Ishai, Dakshita Khurana, Anat Paskin-Cherniavsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


A randomized encoding of a function f(x) is a randomized function f(x, r), such that the “encoding” f(x, r) reveals f(x) and essentially no additional information about x. Randomized encodings of functions have found many applications in different areas of cryptography, including secure multiparty computation, efficient parallel cryptography, and verifiable computation. We initiate a complexity-theoretic study of the class SRE of languages (or boolean functions) that admit an efficient statistical randomized encoding. That is, f(x, r) can be computed in time poly(|x|), and its output distribution on input x can be sampled in time poly(|x|) given f(x), up to a small statistical distance. We obtain the following main results.

Original languageEnglish
Title of host publicationAutomata, Languages, and Programming - 42nd International Colloquium, ICALP 2015, Proceedings
EditorsMagnus M. Halldorsson, Naoki Kobayashi, Bettina Speckmann, Kazuo Iwama
Number of pages13
StatePublished - 2015
Event42nd International Colloquium on Automata, Languages and Programming, ICALP 2015 - Kyoto, Japan
Duration: 6 Jul 201510 Jul 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)


Conference42nd International Colloquium on Automata, Languages and Programming, ICALP 2015

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Statistical randomized encodings: A complexity theoretic view'. Together they form a unique fingerprint.

Cite this