Search Results

Documents authored by Zhou, Chenghan


Document
Analyzing the Economic Impact of Decentralization on Users

Authors: Amit Levy, S. Matthew Weinberg, and Chenghan Zhou

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)


Abstract
We model the ultimate price paid by users of a decentralized ledger as resulting from a two-stage game where Miners (/Proposers/etc.) first purchase blockspace via a Tullock contest, and then price that space to users. When analyzing our distributed ledger model, we find: - A characterization of all possible pure equilibria (although pure equilibria are not guaranteed to exist). - A natural sufficient condition, implied by Regularity (à la [Myerson, 1981]), for existence of a "market-clearing" pure equilibrium where Miners choose to sell all space allocated by the Distributed Ledger Protocol, and that this equilibrium is unique. - The market share of the largest miner is the relevant "measure of decentralization" to determine whether a market-clearing pure equilibrium exists. - Block rewards do not impact users' prices at equilibrium, when pure equilibria exist. But, higher block rewards can cause pure equilibria to exist. We also discuss aspects of our model and how they relate to blockchains deployed in practice. For example, only "patient" users (who are happy for their transactions to enter the blockchain under any miner) would enjoy the conclusions highlighted by our model, whereas "impatient" users (who are interested only for their transaction to be included in the very next block) still face monopoly pricing.

Cite as

Amit Levy, S. Matthew Weinberg, and Chenghan Zhou. Analyzing the Economic Impact of Decentralization on Users. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 93:1-93:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


Copy BibTex To Clipboard

@InProceedings{levy_et_al:LIPIcs.ITCS.2026.93,
  author =	{Levy, Amit and Weinberg, S. Matthew and Zhou, Chenghan},
  title =	{{Analyzing the Economic Impact of Decentralization on Users}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{93:1--93:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.93},
  URN =		{urn:nbn:de:0030-drops-253805},
  doi =		{10.4230/LIPIcs.ITCS.2026.93},
  annote =	{Keywords: Blockchain, Cryptocurrency, Blockspace Markets, Decentralization, Distributed Ledgers, Equilibrium Analysis, Tullock Contests}
}
Document
Profitable Manipulations of Cryptographic Self-Selection Are Statistically Detectable

Authors: Linda Cai, Jingyi Liu, S. Matthew Weinberg, and Chenghan Zhou

Published in: LIPIcs, Volume 316, 6th Conference on Advances in Financial Technologies (AFT 2024)


Abstract
Cryptographic Self-Selection is a common primitive underlying leader-selection for Proof-of-Stake blockchain protocols. The concept was first popularized in Algorand [Jing Chen and Silvio Micali, 2019], who also observed that the protocol might be manipulable. [Matheus V. X. Ferreira et al., 2022] provide a concrete manipulation that is strictly profitable for a staker of any size (and also prove upper bounds on the gains from manipulation). Separately, [Maryam Bahrani and S. Matthew Weinberg, 2024; Aviv Yaish et al., 2023] initiate the study of undetectable profitable manipulations of consensus protocols with a focus on the seminal Selfish Mining strategy [Eyal and Sirer, 2014] for Bitcoin’s Proof-of-Work longest-chain protocol. They design a Selfish Mining variant that, for sufficiently large miners, is strictly profitable yet also indistinguishable to an onlooker from routine latency (that is, a sufficiently large profit-maximizing miner could use their strategy to strictly profit over being honest in a way that still appears to the rest of the network as though everyone is honest but experiencing mildly higher latency. This avoids any risk of negatively impacting the value of the underlying cryptocurrency due to attack detection). We investigate the detectability of profitable manipulations of the canonical cryptographic self-selection leader selection protocol introduced in [Jing Chen and Silvio Micali, 2019] and studied in [Matheus V. X. Ferreira et al., 2022], and establish that for any player with α < (3-√5)/2 ≈ 0.38 fraction of the total stake, every strictly profitable manipulation is statistically detectable. Specifically, we consider an onlooker who sees only the random seed of each round (and does not need to see any other broadcasts by any other players). We show that the distribution of the sequence of random seeds when any player is profitably manipulating the protocol is inconsistent with any distribution that could arise by honest stakers being offline or timing out (for a natural stylized model of honest timeouts).

Cite as

Linda Cai, Jingyi Liu, S. Matthew Weinberg, and Chenghan Zhou. Profitable Manipulations of Cryptographic Self-Selection Are Statistically Detectable. In 6th Conference on Advances in Financial Technologies (AFT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 316, pp. 30:1-30:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


Copy BibTex To Clipboard

@InProceedings{cai_et_al:LIPIcs.AFT.2024.30,
  author =	{Cai, Linda and Liu, Jingyi and Weinberg, S. Matthew and Zhou, Chenghan},
  title =	{{Profitable Manipulations of Cryptographic Self-Selection Are Statistically Detectable}},
  booktitle =	{6th Conference on Advances in Financial Technologies (AFT 2024)},
  pages =	{30:1--30:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-345-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{316},
  editor =	{B\"{o}hme, Rainer and Kiffer, Lucianna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2024.30},
  URN =		{urn:nbn:de:0030-drops-209660},
  doi =		{10.4230/LIPIcs.AFT.2024.30},
  annote =	{Keywords: Blockchain, Cryptocurrency, Proof-of-Stake, Strategic Mining, Statistical Detection}
}
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail