This paper identifies and resolves a critical architectural flaw in citation-weighted reputation systems operating within Weighted Directed Acyclic Graph (WDAG) governance structures for Decentralized Autonomous Organizations (DAOs). Under existing formulations, rational agents face a direct financial disincentive to cite prior contributions, as citation-weighted value allocation through PageRank-derived mechanisms transfers economic reward from the citing agent to the cited agent. This under-citation incentive undermines the foundational promise of knowledge attribution in decentralized collaborative systems. The paper formalizes the under-citation problem, demonstrates the impossibility of precise citation quantification, and identifies a gap in existing game-theoretic proofs that purport to establish citation honesty as an equilibrium. Drawing on the WDAG governance framework developed in Calcaterra (2018), this paper proposes an integrated solution that decouples citation accuracy from quality-based payment, introduces validator-assessed citation honesty as a separately ranked and rewarded dimension, and establishes retroactive audit mechanisms with graduated sanctions. A new equilibrium theorem (Theorem 3b) demonstrates that under the integrated solution, honest citation constitutes a Nash equilibrium when validators assess citation accuracy and the marginal effect of citation accuracy on validator-assessed honesty scores exceeds the marginal gain from self-citation inflation. The paper situates these findings within the broader framework of dynamic regulation theory and New Institutional Economics incomplete contract theory, arguing that static citation protocols are inherently vulnerable to gaming and that evolutionary governance mechanisms are essential for sustaining honest knowledge attribution in decentralized systems.
Decentralized Autonomous Organizations (DAOs) are digital communities that make collective decisions by voting on blockchain communication-systems, amongst other coordination media. "Token voting" is intended to, on the one hand, efficiently synthesize individuals' limited information toward collective intelligence, on the other, it is presented as an inclusive approach to the governance of organizations-allowing any member with tokens to voice their opinions. In this latter sense, DAO decision-making is described as 'decentralized governance,' a misnomer, as most DAOs exhibit extreme centralization in token allocation. Yet, this paper finds value in DAO's collective decision-making intentions: the core blockchain infrastructure, when paired with a DAO's collective voting, produces an immutable, peerproduced ledger of group decision-making. Much empirical and theoretical attention has focused on consensus, understood as the majority-supported outcome of a vote. This paper argues that such a focus is incomplete. Consensus is often treated as a signal of a collective's certainty in a chosen outcome, yet this certainty depends on the structure of the decision space. The same majority share can imply different levels of certainty depending on the number of available options and how support is distributed across non-winning alternatives. As such, collective decisions cannot be evaluated by majority size alone, but must be understood relative to how a community allocates support across the full set of choices. To this end, this paper proposes the Rényi family of entropy-based measures, along with several derived metrics, as tools to map the topology of consensus and disagreement. It applies these metrics to voting data from 277 DAOs to signal (1) whether dissenting opinions converge into coordinated blocks of collective opposition or disperse pluralistically across the decision space, and (2) the effective number of choices and relative weight of substantively engaged alternatives within the choice set. The former heuristic qualifies the type of disagreement to ask "did disagreement converge into viable minority alternatives?" The latter heuristic quantifies the number of options that were seriously considered, and to what degree?" Altogether, this paper contributes a formal information-theoretic framework for representing the topology of collective decision-making through the distribution of support across all alternatives. It provides heuristics that treat a community's decision-making quality as a design question and enables majority outcomes to be interpreted relative to how support is distributed across the full set of choices, rather than in isolation.
<b>Proof-of-Stake (PoS) security models</b> assume validator independence, decentralized decision-making, and economically rational but non-coordinated behavior. This paper introduces <b><i>Shadow Validator Cartels</i></b>, a class of covert consensus capture attacks in which validators coordinate off-chain to influence block production, transaction ordering, and governance outcomes while remaining individually protocol-compliant. Unlike explicit majority or 51% attacks, shadow cartels do not require dominant stake ownership or on-chain collusion. Instead, they leverage shared infrastructure, aligned economic incentives, and soft coordination mechanisms that render their behavior statistically indistinguishable from organic validator activity. We analyze the structural enablers, formation mechanics, and systemic impacts of shadow validator cartels, demonstrate why existing decentralization metrics fail to detect them, and outline system-level mitigation requirements necessary to preserve credible neutrality in PoS networks.
Stefano Balietti, Pietro Saggese, Markus Strohmaier
Decentralized Autonomous Organizations (DAOs) use token-weighted voting to allocate resources, set protocol rules, and legitimate collective decisions. Yet, support in DAO voting is strikingly concentrated. What happens inside the ballot that produces this concentration? We study DAOs' governance at the proposal-choice level, linking each choice's voting-power share to three observable features: whether it expresses an approval-oriented stance, where it appears in the choice list, and whether it is selected by the proposal author. We find that (i) author-selected choices show the strongest and most robust association with voting-power share, with a 58.8% increase relative to non-author choices; (ii) approval-oriented choices retain a positive but slightly less consistent advantage (27.1%); and (iii) first-listed choices also attract systematically higher shares, consistent with position and order effects (7.7%). Results are robust across several specifications, which include subtracting an author's own voting power from computations. We use bias descriptively, to denote systematic associations rather than proven causal distortion. The results shift attention from proposal outcomes alone to the interface and social signals through which choices are presented. In DAO governance, ordering, author signals, and vote visibility should be treated as institutional design choices, not neutral implementation details.
This paper examines the strategic behavior of rational actors in the TON blockchain, focusing on their responses to slashing mechanisms in a proof-of-stake (PoS) environment. Slashing introduces financial penalties for behavior that threatens network integrity, addressing the nothing-at-stake problem, where validators in PoS systems can support multiple chains at no cost. Although slashing is intended to deter malicious behavior by Byzantine actors, it also affects rational validators by altering their expected returns. Using a game-theoretic model inspired by the BAR framework, this study examines how rational, utility-maximizing validators weigh the risks and rewards of violating or enforcing slashing mechanisms in the presence of potentially Byzantine actors when penalty enforcement is uncertain. Located at the intersection of game theory and distributed systems, this research sheds light on compliance and deviation dynamics in PoS networks, contributing to a deeper understanding of incentive alignment in blockchain governance.
Concentrated-liquidity automated market makers (CLAMMs), as exemplified by Uniswap v3, are now a common primitive in decentralized finance frameworks. Their design combines continuous trading on constant-function curves with discrete tick boundaries at which liquidity positions change and rounding effects accumulate. While there is a body of economic and game-theoretic analysis of CLAMMs, there is negligible work that treats Uniswap v3 at the level of formal state machines amenable to model checking or theorem proving. In this paper we propose a formal modeling approach for Uniswap v3-style CLAMMs using (i) networks of priced timed automata (PTA), and (ii) finite-state transducers (FST) over discrete ticks. Positions are treated as stateful objects that transition only when the pool price crosses the ticks that bound their active range. We show how to encode the piecewise constant-product invariant, fee-growth variables, and tick-crossing rules in a PTA suitable for tools such as UPPAAL, and how to derive a tick-level FST abstraction for specification in TLA+. We define an explicit tick-wise invariant for a discretized, single-tick CLAMM model and prove that it is preserved up to a tight additive rounding bound under fee-free swaps. This provides a formal justification for the "$ε$-slack" used in invariance properties and shows how rounding enters as a controlled perturbation. We then instantiate these models in TLA+ and use TLC to exhaustively check the resulting invariants on structurally faithful instances, including a three-tick concentrated-liquidity configuration and a bounded no-rounding-only-arbitrage property in a bidirectional single-tick model. We discuss how these constructions lift to the tick-wise structure of Uniswap v3 via virtual reserves, and how the resulting properties can be phrased as PTA/TLA+ invariants about cross-tick behaviour and rounding safety.
Committees are extensively used in the designs of various Proof-of-Stake (PoS) blockchains. A committee is simply a randomly selected subset of the parties/nodes in the system. Ideally, the committee should i) be as small as possible, and ii) properly represent the entire system, in terms of the corruption ratio. Existing committee selection schemes all follow the principle of proportionality, which says that a committee member should neither over-represent nor under-represent the stake it holds.
András Nagy, János Tapolcai, István András Seres, Bence Ladóczki
Proof-of-stake consensus protocols often rely on distributed randomness beacons (DRBs) to generate randomness for leader selection. This work analyses the manipulability of Ethereum's DRB implementation, RANDAO, in its current consensus mechanism. Even with its efficiency, RANDAO remains vulnerable to manipulation through the deliberate omission of blocks from the canonical chain. Previous research has shown that economically rational players can withhold blocks known as a block withholding attack or selfish mixing when the manipulated RANDAO outcome yields greater financial rewards.
The article examines the problem of balancing security and flexibility in decision-making mechanisms within decentralized autonomous organizations (DAOs), which operate without centralized control through the use of smart contracts. To this end, two main voting models employed in DAOs are analyzed: the conjunctive model, which requires unanimous approval of a proposal by all participant groups, and the disjunctive model, where approval from a single group is sufficient. Both models have significant advantages and drawbacks: the former ensures a high level of security and protection of all parties’ interests but considerably slows down the decision-making process, while the latter provides speed and scalability but introduces risks of centralized influence. In response to these challenges, a hybrid voting model is proposed, in which the type of logic is determined by the nature of the proposal. Specifically, critical changes, such as updates to governance rules or quorum parameters, must involve all groups, whereas routine operational matters can be decided through a simplified disjunctive procedure. The implemented smart contract architecture supports both mechanisms and enables DAOs to dynamically adjust quorum thresholds through separate governance proposals. To evaluate the effectiveness of the model, a simulation of 1,000 voting processes was conducted under four different scenarios of participant activity: balanced, one-sided, and low overall participation. The results showed a reduction in the probability of deadlock situations and an increase in the share of successful votes when hybrid logic was applied, particularly under conditions of low or asymmetric participation. In addition, special attention was given to gas cost optimization: the disjunctive approach allows vote counting to be stopped once a quorum is reached by one group, thus reducing overall computational expenses. Therefore, the proposed solution appears promising for both financial DAOs and decentralized infrastructures, particularly the Internet of Things, where speed, scalability, and secure coordination are especially important.
Lending protocols are one of the main applications of Decentralized Finance (DeFi), enabling crypto-assets loan markets with a total value estimated in the tens of billions of dollars. Unlike traditional lending systems, these protocols operate without relying on trusted authorities or off-chain enforcement mechanisms. To achieve key economic goals such as stability of the loan market, they devise instead trustless on-chain mechanisms, such as rewarding liquidators who repay the loans of under-collateralized borrowers by awarding them part of the borrower's collateral. The complexity of these incentive mechanisms, combined with their entanglement in low-level implementation details, makes it challenging to precisely assess the structural and economic properties of lending protocols, as well as to analyze user strategies and attacks. Crucially, since participation is open to anyone, any weaknesses in the incentive mechanism may give rise to unintended emergent behaviours, or even enable adversarial strategies aimed at making profits to the detriment of legit users, or at undermining the stability of the protocol. In this work, we propose a formal model of lending protocols that captures the essential features of mainstream platforms, enabling us to identify and prove key properties related to their economic and strategic dynamics.
In this article, we propose a new form of decentralized autonomous organization (DAO) governance that uses a sequential auction mechanism to overcome the entrenched control issues that have emerged for DAOs by creating a regime of temporary contestable control. The mechanism avoids potential public choice problems inherent in voting approaches but at the same time provides a vehicle that can enhance and secure value that inheres to DAO voting and other DAO non-market governance procedures. It is robust to empty voting and is code feasible. The mechanism not only facilitates the ability of DAOs to meet their normative and operational goals in the face of diverse regulatory approaches, but also strengthens the case for creating a less burdensome but at least equally effective regulatory regime for DAOs that employ the mechanism. Designed to shift control to the party with the most promising business plan, at the same time, it deters value destruction by control parties, maximizes social surplus, and distributes that surplus in a way that tends to promote investment by other parties both at start up and on an ongoing basis.
We develop and apply epistemic tests to various decentralized governance methods as well as to study the impact of participation. These tests probe the ability to reach a correct outcome when there is one. We find that partial abstention is a strong governance method from an epistemic standpoint compared to alternatives such as various forms of ``transfer delegation" in which voters explicitly transfer some or all of their voting rights to others. We make a stronger case for multi-step transfer delegation than is present in previous work but also demonstrate that transfer delegation has inherent epistemic weaknesses. We show that enhanced direct participation, voters exercising their own voting rights, can have a variety of epistemic impacts, some very negative. We identify governance conditions under which additional direct participation is guaranteed to do no epistemic harm and is likely to increase the probability of making correct decisions. In light of the epistemic challenges of voting-based decentralized governance, we consider the possible supplementary use of prediction markets, auctions, and AI agents to improve outcomes. All these results are significant because epistemic performance matters if entities such as DAOs (decentralized autonomous organizations) wish to compete with organizations that are more centralized.
Lukas Weidener, Fabio Laredo, K. I. Pavan Kumar, Karlin Compton
This study presents a systematic scoping review of delegated voting (DV) in decentralized autonomous organizations (DAOs), focusing on its governance implications, implementation forms, and challenges. DV refers to a mechanism through which token holders transfer their voting rights to other participants, often called delegates, who vote on their behalf. While DV is often adopted to address low participation and mitigate the cognitive burden of direct involvement, the existing literature highlights its potential to exacerbate centralization, particularly when whales or influential networks are disproportionate. This creates tension between the intended efficiency gains of the delegation and the unintended concentration of power. Various implementation models, including off-chain platforms (e.g., Snapshot), hybrid governance architectures, and token-based delegation systems, exhibit distinct trade-offs in transparency, cost, and adaptability. Although innovations such as quadratic voting, weighted delegation constraints, and reputation-based governance show promise for improving fairness and accountability, they also face vulnerabilities, such as gaming, collusion, and high implementation complexity. To explore the diverse approaches to DV, this review organizes and synthesizes key findings from recent scholarly publications examining its implementation, risks, and governance outcomes. Synthesizing insights from 13 publications, this review identifies key governance trade-offs, implementation patterns, and risks associated with DV. It also outlines future research directions, including multi-tiered governance structures and decision-support mechanisms, to guide more inclusive and context-aware DAO governance.
With complete-information bilateral bargaining in network settings, holdup is eliminated when contracts across the network are agreed atomically (all or none) via a smart contract. Applications include over-the-counter trading, syndicated lending, multi-tranche securitizations, third-party financed purchases, and bookbuilding. Under a novel extensive-form bargaining protocol, any firm can give a “greenlight” to the terms of a contract proposed to that firm, which automatically converts those terms into a binding contract if the terms proposed to all other firms also receive greenlights. In any Perfect Bayesian Equilibrium with Markov strategies, firms immediately agree on socially efficient contracts that equalize expected gains across firms.
In decentralized governance, existing token-based voting mechanisms employed by Decentralized Autonomous Organizations (DAOs) often suffer from centralization risks, as a small number of large token holders can dominate decision-making. While reputation-based voting has emerged as an alternative that reflects members’ historical contributions, it is also prone to ossification, where early contributors accumulate disproportionate influence over time. To address these challenges, we propose a novel hybrid dynamic voting mechanism that combines tokens and reputation in the voting power. Furthermore, we incorporate an exponential decay mechanism into the reputation component to ensure that voting power dynamically reflects recent and active participation rather than legacy status. We also utilize Gini and Nakamoto coefficients to evaluate the proposed mechanism. To validate our proposed mechanism, we design some computational experiments, and the experimental results show that the proposed hybrid mechanism achieves better fairness and decentralization, while allowing new contributors to more quickly gain meaningful influence. This work provides insights into designing adaptive, fair, and secure governance mechanisms for DAOs.
Roozbeh Sarenche, Alireza Aghabagherloo, Svetla Nikova⋆, Bart Preneel
The security of Bitcoin protocols is deeply dependent on the incentives provided to miners, which come from a combination of block rewards and transaction fees. As Bitcoin experiences more halving events, the protocol reward converges to zero, making transaction fees the primary source of miner rewards. This shift in Bitcoin's incentivization mechanism, which introduces volatility into block rewards, leads to the emergence of new security threats or intensifies existing ones. Previous security analyses of Bitcoin have either considered a fixed block reward model or a highly simplified volatile model, overlooking the complexities of Bitcoin's mempool behavior. This paper presents a reinforcement learning-based tool to develop mining strategies under a more realistic volatile model. We employ the Asynchronous Advantage Actor-Critic (A3C) algorithm, which efficiently handles dynamic environments, such as the Bitcoin mempool, to derive near-optimal mining strategies when interacting with an environment that models the complexity of the Bitcoin mempool. This tool enables the analysis of adversarial mining strategies, such as selfish mining and undercutting, both before and after difficulty adjustments, providing insights into the effects of mining attacks in both the short and long term. We revisit the Bitcoin security threshold presented in the WeRLman paper and demonstrate that the implicit predictability of valuable transaction arrivals in this model leads to an underestimation of the reported threshold. Additionally, we show that, while adversarial strategies like selfish mining under the fixed reward model incur an initial loss period of at least two weeks, the transition toward a transaction-fee era incentivizes mining pools to abandon honest mining for immediate profits. This incentive is expected to become more significant as the protocol reward approaches zero in the future.
This paper introduces the Voting with Random Proposers (VRP) procedure to address the challenges of agenda manipulation in voting. In each round of VRP, a randomly selected proposer suggests an alternative that is voted on against the previous round's winner. In a framework with single-peaked preferences, we show that the VRP procedure guarantees that the Condorcet winner is implemented in a few rounds with truthful voting, and in just two rounds under sufficiently symmetric preference distributions or if status quo positions are not extreme. The results have applications for committee decisions, legislative decision-making, and the organization of citizens' assemblies and decentralized autonomous organizations.
Grigorii Melnikov, Sebastian Müller, Nikita Polyanskii, Yury Yanovich
Consensus plays a crucial role in distributed ledger systems, impacting both scalability and decentralization. Many blockchain systems use a weighted lottery based on a scarce resource such as a stake, storage, memory, or computing power to select a committee whose members drive the consensus and are responsible for adding new information to the ledger. Therefore, ensuring a robust and fair committee selection process is essential for maintaining security, efficiency, and decentralization. There are two main approaches to randomized committee selection. In one approach, each validator candidate locally checks whether they are elected to the committee and reveals their proof during the consensus phase. In contrast, in the second approach, a sortition algorithm decides a fixed-sized committee that is globally verified. This paper focuses on the latter approach, with cryptographic sortition as a method for fair committee selection that guarantees a constant committee size. Our goal is to develop deterministic guarantees that strengthen decentralization. We introduce novel methods that provide deterministic bounds on the influence of adversaries within the committee, as evidenced by numerical experiments. This approach overcomes the limitations of existing protocols that only offer probabilistic guarantees, often providing large committees that are impractical for many quorum-based applications like atomic broadcast and randomness beacon protocols.
Perpetual voting studies fair collective decision-making in settings where many decisions are to be made, and is a natural framework for settings such as parliaments and the running of blockchain Decentralized Autonomous Organizations (DAOs). We focus our attention on the binary case (YES/NO decisions) and \textit{individual} guarantees for each of the participating agents. We introduce a novel notion, inspired by the popular maxi-min-share (MMS) for fair allocation. The agent expects to get as many decisions as if they were to optimally partition the decisions among the agents, with an adversary deciding which of the agents decides on what bundle. We show an online algorithm that guarantees the MMS notion for $n=3$ agents, an offline algorithm for $n=4$ agents, and show that no online algorithm can guarantee the $MMS^{adapt}$ for $n\geq 7$ agents. We also show that the Maximum Nash Welfare (MNW) outcome can only guarantee $O(\frac{1}{n})$ of the MMS notion in the worst case.
Instant Runoff Voting (IRV) is one example of ranked-choice voting. It provides many known benefits when used in elections, such as minimising vote splitting, ensuring few votes are wasted, and providing resistance to strategic voting. However, the voting and tallying procedures for IRV are much more complicated than those of plurality and are both error-prone and tedious. Many automated systems have been proposed to simplify these procedures in IRV. Some of these also employ cryptographic techniques to protect the secrecy of ballots and enable verification of the tally. Nearly all of these cryptographic systems require a set of trustworthy tallying authorities (TAs) to perform the decryption of votes and/or running of mix servers, which adds significant complexity to the implementation and election management. We address this issue by proposing Camel: an E2E verifiable solution for IRV that requires no TAs. Camel employs a novel representation and a universally verifiable shifting procedure for ballots that facilitate the elimination of candidates as required in an IRV election. We combine these with a homomorphic encryption scheme and zero-knowledge proofs to protect the secrecy of the ballots and enable any party to verify the well-formedness of the ballots and the correctness of the tally in an IRV election. We examine the security of Camel and prove it maintains ballot secrecy by limiting the learned information (namely the tally) against a set of colluding voters.
Georgios Birmpas, Philip Lazos, Evangelos Markakis, Paolo Penna
In this paper, we investigate the impact of reward schemes and committee sizes motivated by governance systems over blockchain communities. We introduce a model for elections with a binary outcome space where there is a ground truth (i.e., a "correct" outcome), and where stakeholders can only choose to delegate their voting power to a set of delegation representatives (DReps). Moreover, the effort (cost) invested by each DRep positively influences both (i) her ability to vote correctly and (ii) the total delegation that she attracts, thereby increasing her voting power. This model constitutes the natural counterpart of delegated proof-of-stake (PoS) protocols, where delegated stakes are used to elect the block builders. As a way to motivate the representatives to exert effort, a reward scheme can be used based on the delegation attracted by each DRep. We analyze both the game-theoretic aspects and the optimization counterpart of this model. Our primary focus is on selecting a committee that maximizes the probability of reaching the correct outcome, given a fixed monetary budget allocated for rewarding the delegates. Our findings provide insights into the design of effective reward mechanisms and optimal committee structures (i.e., how many DReps are enough) in these PoS-like governance systems.