About

Joseph Bonneau is a faculty member in the Crypto and Security Group at NYU Courant. His research focuses on applied cryptography, cryptocurrencies, verifiable lotteries, and secure messaging. As part of the group, he contributes to advancing the understanding and development of cryptographic applications and protocol design, bridging fundamental theory with practical implementations in security and cryptography.

Research topics

• Computer Science
• Computer Security
• Geology
• Philosophy
• Seismology
• Algorithm
• Geography
• Computer network
• Distributed computing
• Cartography

Selected publications

• Publisher Correction: Reproducibility and robustness of economics and political science research

  Nature · 2026-04-23

  articleOpen access
  PublisherOA PDFDOI

• Publisher Correction: Reproducibility and robustness of economics and political science research

  Figshare · 2026-04-23

  articleOpen access

  Publisher Correction: Reproducibility and robustness of economics and political science research

  PublisherDOI

• SoK: Cryptographic Authenticated Dictionaries

  2026-01-01

  articleOpen access

  We systematize the research on authenticated dictionaries (ADs)-cryptographic data structures that enable applications such as key transparency, binary transparency, verifiable key-value stores, and integrity-preserving filesystems.First, we present a unified framework that captures the trust and threat assumptions behind five common deployment scenarios.Second, we distill and reconcile the diverse security definitions scattered across the literature, clarifying the guarantees they offer and when each is appropriate.Third, we develop a taxonomy of AD constructions and analyze their asymptotic costs, exposing a sharp dichotomy: every known scheme either incurs O(log n) time for both lookups and updates, or achieves O(1) for one operation only by paying O(n) for the other.Surprisingly, this barrier persists even when stronger trust assumptions are introduced, undermining the intuition that "more trust buys efficiency".We conclude with application-driven research questions, including realistic auditing models and incentives for adoption in systems that today provide no verifiable integrity at all.

  PublisherDOI

• Reproducibility and robustness of economics and political science research

  Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) · 2026-01-01

  articleOpen access

  Science aspires to be cumulative. Reproducibility efforts strengthen science by testing the reliability of published findings, promoting self-correction, and informing policy-making. Computational reproductions, whereby independent researchers reproduce the results of published studies, are an essential diagnostic tool. Such efforts should have greater visibility. However, little social science reproduction and robustness has been conducted at scale. Here we reproduced original analyses and conducted robustness checks of 110 articles that were published in leading economics and political science journals with mandatory data and code sharing policies. We found that more than 85% of published claims were computationally reproducible. In robustness checks, our reanalyses showed that 72% of statistically significant estimates remain significant and in the same direction, and the median reproduced effect size is nearly the same as the originally published effect size (that is, 99% of the published effect size). Additionally, 6 independent research teams examined 12 pre-specified hypotheses about determinants of robustness. Research teams with more experience found lower levels of robustness, and robustness did not correlate with author characteristics or data availability.

  PublisherDOI

• Reproducibility and robustness of economics and political science research

  Nature · 2026-04-01 · 5 citations

  articleOpen access
  PublisherOA PDFDOI

• SoK: Trusted Setups for Powers-of-Tau Strings

  Lecture notes in computer science · 2026-01-01

  book-chapterSenior author
  PublisherDOI

• Short Paper: Naysayer Proofs

  Lecture notes in computer science · 2025-01-01 · 1 citations

  book-chapterSenior author
  PublisherDOI

• Good Things Come to Those Who Wait

  Lecture notes in computer science · 2025-01-01 · 2 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• Verde: Verification via Refereed Delegation for Machine Learning Programs

  ArXiv.org · 2025-02-26

  preprintOpen accessSenior author

  Machine learning programs, such as those performing inference, fine-tuning, and training of LLMs, are commonly delegated to untrusted compute providers. To provide correctness guarantees for the client, we propose adapting the cryptographic notion of refereed delegation to the machine learning setting. This approach enables a computationally limited client to delegate a program to multiple untrusted compute providers, with a guarantee of obtaining the correct result if at least one of them is honest. Refereed delegation of ML programs poses two technical hurdles: (1) an arbitration protocol to resolve disputes when compute providers disagree on the output, and (2) the ability to bitwise reproduce ML programs across different hardware setups, For (1), we design Verde, a dispute arbitration protocol that efficiently handles the large scale and graph-based computational model of modern ML programs. For (2), we build RepOps (Reproducible Operators), a library that eliminates hardware "non-determinism" by controlling the order of floating point operations performed on all hardware. Our implementation shows that refereed delegation achieves both strong guarantees for clients and practical overheads for compute providers.

  PublisherOA PDFDOI

• Breaking Omertà: On Threshold Cryptography, Smart Collusion, and Whistleblowing

  2025-11-19 · 1 citations

  articleOpen access

  Cryptographic protocols often make honesty assumptions---e.g., fewer than t out of n participants are adversarial. In practice, these assumptions can be hard to ensure, particularly given monetary incentives for participants to collude and deviate from the protocol.

  PublisherDOI

Frequent coauthors

• Edward W. Felten

  11 shared

• Jeremy Clark

  10 shared

• Dan Boneh

  Stanford University

  9 shared

• Frank Stajano

  9 shared

• Jonathan Anderson

  Memorial University of Newfoundland

  9 shared

• Arvind Narayanan

  8 shared

• Sören Preibusch

  7 shared

• Benedikt Bünz

  5 shared

Labs

• NYU Crypto & Sec GroupPI

  Researches all aspects of cryptography and security, from fundamental theory to novel cryptographic applications and protocol design.

Awards & honors

• USENIX Security 2015
• USENIX Security 2022
• USENIX Security 2024
• ACM CCS 2022
• ACM CCS 2024