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Privacy-Preserving Inclusion Lists

Authors Zhengwei Tong , Saba Eskandarian , Kartik Nayak

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Subject Classification

ACM Subject Classification
  • Security and privacy → Privacy-preserving protocols
Keywords
  • Blockchain
  • Inclusion List
  • Privacy
  • Multiparty Computation
  • Censorship Resistance

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Abstract

Blockchains aim to provide open access and censorship resistance, but centralization of block production in blockchains like Ethereum undermines these goals. Inclusion List (IL) protocols mitigate this by requiring block proposers to include transactions selected by an IL committee to enforce the inclusion of transactions that appear to have been censored. However, protecting the confidentiality of individual committee members’ contributions is essential to prevent retaliation and ensure robust censorship resistance.
We propose a lightweight, privacy-preserving inclusion list protocol that allows committees to collectively construct transaction lists while hiding individual contributions and ensuring plausible deniability. Our approach builds on multiparty computation (MPC) techniques to achieve strong privacy without relying on heavyweight cryptography or anonymous broadcast channels.
We implement two variants of our protocol design: an optimistic version providing malicious security with abort (latency ∼ 4.0s) for speed, and a robust variant (latency ∼ 124.7s) for guaranteed output delivery in the presence of a Byzantine threshold of t < n/3 malicious parties.

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Zhengwei Tong, Saba Eskandarian, and Kartik Nayak. Privacy-Preserving Inclusion Lists. In 8th Conference on Advances in Financial Technologies (AFT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 395, pp. 2:1-2:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.AFT.2026.2

Author Details

Zhengwei Tong
  • Duke University, Durham, NC, USA
Saba Eskandarian
  • University of North Carolina at Chapel Hill, NC, USA
Kartik Nayak
  • Duke University, Durham, NC, USA

Funding

This material is based upon work supported by the National Science Foundation under Award Nos. 2234408 and 2237814. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Supplementary Materials

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