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Towards Characterizing Secure Samplability

Authors: Hari Krishnan P. Anilkumar, Keval Jain, Manoj Prabhakaran, and Vinod M. Prabhakaran

Published in: LIPIcs, Volume 385, 7th Conference on Information-Theoretic Cryptography (ITC 2026)


Abstract
This work deals with the fundamental problem of characterizing which multiparty distributions can be securely sampled with information-theoretic security against passive corruption, when there is no setup or honest-majority. We focus on the case of 4-party distributions with boolean outputs for each party. We show that such a distribution is securely samplable if and only if every 2-party distribution derived from it by partitioning the parties into two sets is securely samplable. This extends a similar characterization previously known for 3-party distributions.

Cite as

Hari Krishnan P. Anilkumar, Hari Krishnan P. Anilkumar, Keval Jain, Keval Jain, Manoj Prabhakaran, Manoj Prabhakaran, Vinod M. Prabhakaran, and Vinod M. Prabhakaran. Towards Characterizing Secure Samplability. In 7th Conference on Information-Theoretic Cryptography (ITC 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 385, pp. 6:1-6:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{anilkumar_et_al:LIPIcs.ITC.2026.6,
  author =	{Anilkumar, Hari Krishnan P. and Jain, Keval and Prabhakaran, Manoj and Prabhakaran, Vinod M.},
  title =	{{Towards Characterizing Secure Samplability}},
  booktitle =	{7th Conference on Information-Theoretic Cryptography (ITC 2026)},
  pages =	{6:1--6:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-426-0},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{385},
  editor =	{Dodis, Yevgeniy},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITC.2026.6},
  URN =		{urn:nbn:de:0030-drops-270991},
  doi =		{10.4230/LIPIcs.ITC.2026.6},
  annote =	{Keywords: secure sampling, information-theoretic MPC}
}
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