Romulo de Moraes, Arthur G. Bubolz, Denner Ayres, Vinícius Teixeira Pinto · 5 authors
Este artigo apresenta uma arquitetura para loterias descentralizadas na rede Ethereum, baseada em contratos inteligentes, aleatoriedade verificável e otimização de armazenamento por meio de Merkle Tree. A proposta visa reduzir o custo médio das transações (gas fees) e aprimorar a escalabilidade onchain, comparando três abordagens distintas de armazenamento: array, mapping e Merkle Tree. Os resultados mostram que o consumo de gas evidencia uma vantagem expressiva da Merkle Tree, reduzindo em até três ordens de magnitude o custo total, o que confirma sua eficiência e potencial para aplicações descentralizadas de alta demanda.
Abstract - The paper referenced proposes a decentralized marketplace model for trading, verifying, and managing the ownership of AI models by means of blockchain and NFTs. Given the need for trusted exchange and provenance in the management of AI assets, the authors propose a system wherein AI models and datasets are represented as NFTs on a public blockchain, providing transparent, traceable, and secure transactions. Smart contracts automate auctions, royalty distributions, and ownership transfers. Further security and privacy are provided by TEEs, proxy re-encryption, and decentralized storage (IPFS). Collaboration is enabled through the architecture, which allows contributors to improve and resell models, while royalty schemes guarantee fair compensation for creators. Details of the implementation include smart contracts in Solidity and cost analyses for transaction efficiency. Evaluation in terms of security is resilient against Sybil and Eclipse threats. It is also set up as broadly adaptable to both public and private AI assets and easily generalizable to other situations of digital assets to ensure robust provenance, fair remuneration, and trustless exchange. Key Words: Blockchain, Non-Fungible Tokens(NFTs), Decentralized AI marketplace, Smart Contracts, Digital Ownership
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.
We present the Proof of Fairness Ledger (PoFL), a unified cryptographic framework for decentralized sealed-bid auctions that jointly ensures privacy, input fairness, output correctness, and public verifiability. PoFL separates a minimal Commit-Open-Verify pipeline from optional extensions, keeping the core lightweight while enabling stronger auditability when required. Its central construct, the frozen root snapshot R*, instantiated as a Merkle-style hash accumulator, immutably binds all timely commitments before the opening phase and serves as a public anchor for verification. After opening, correctness can be proven either by direct bid comparison or by a succinct Zero-Knowledge Proof of Winner, which attests inclusion, commitment consistency, and bid maximality with respect to R*. We analyze PoFL under standard cryptographic assumptions - discrete logarithm hardness, collision-resistant hashing, and the Random Oracle Model—and discuss practical efficiency for on-chain and off-chain deployment. Constant-size verification and logarithmic inclusion proofs make PoFL suitable for smart-contract implementation. Additionally, PoFL can integrate dynamic collateral management and optional force-open mechanisms to ensure liveness and economic accountability. Overall, PoFL provides a practical and theoretically grounded approach to transparent, auditable, and privacy-preserving auctions in permissionless environments.
Decentralized Autonomous Organizations (DAOs) overwhelmingly use token-weighted voting as their core governance mechanism. Empirical evidence reveals that this approach often leads to plutocratic governance, with voting power concentrated among a few large holders. Traditional models exacerbate this dilemma: on-chain voting is transparent but costly, marginalizing small participants, while off-chain mechanisms lower participation costs but rely on trusted multi-signature execution, reintroducing centralization. To resolve this trilemma of decentralization, efficiency, and trust, we propose a VoS. VoS introduces a trust-minimized aggregation model tailored for DAO governance: votes are collected offchain and aggregated into a constant-size proof that smart contracts verify in $O(1)$ time, thereby enabling fully on-chain execution without intermediaries. Although VoS cannot eliminate the plutocracy rooted in token distribution, it prevents governance mechanisms from amplifying it, charting a practical path toward secure, efficient, and trust-minimized DAO governance.
Introduction: Since its inception with Bitcoin in 2008, blockchain technology has evolved into a foundational infrastructure for secure, transparent, and decentralized systems across various sectors, including finance, supply chains, healthcare, and the internet of things (IoT). The introduction of Ethereum and smart contracts in 2015 catalyzed the development of decentralized applications (DApps) and decentralized autonomous organizations (DAOs), significantly expanding blockchain’s utility. Methods: A new blockchain trend is being created to address IoT applications requiring fast transaction processing accuracy. It is built on fast consensus mechanisms, including PBFT, sharding, the clustering principle, and the parallel execution of smart contracts Results: In this paper, we address the problems of parallel transaction execution consistency with respect to having the same transaction and smart contract execution order. Discussion: We analyze how current consensus mechanisms affect transaction ordering and explore methods to ensure deterministic execution without compromising speed or scalability. Conclusion: We propose a new algorithm called unordered global distributed transaction, which is based on order verification instead of time-consuming transaction consensus ordering.
Smart contracts enable programmatic agreements but face two persistent problems: high on-chain cost (throughput/latency) and weak privacy (public ledger exposes transaction semantics). We propose a hybrid on-chain/off-chain commitment scheme (HOC-C) that combines lightweight on-chain commitments, verifiable off-chain computation, and succinct zero-knowledge proofs to deliver privacy-preserving contract execution at scale. In HOC-C, sensitive inputs and heavy computations are executed off-chain by a consortium of replicated verifiers; the verifiers publish a succinct zk-SNARK proof of correct execution plus a small state commitment on-chain. The on-chain contract verifies the proof and updates state atomically. To prevent malicious collusion among verifiers, HOC-C integrates an economic incentive layer and challenge windows where anyone can publish refutation proofs; the refutation burden is designed to be less than the honest-verifier cost. We implement HOC-C using a prototype that plugs into an EVM-compatible chain (Ethereum testnet) and evaluate performance for representative workloads (private auctions, confidential supply-chain workflows, private token-transfer batching). The system reduces gas cost by an order of magnitude compared to naive on-chain execution while preserving end-to-end confidentiality for user inputs. We analyze security properties (soundness, liveness, and economic incentive compatibility) and discuss trade-offs: proof generation latency vs. throughput, verifier decentralization vs. amortized cost. HOC-C offers a practical roadmap for adopting private, inexpensive smart contracts on mainstream blockchains.
Marko Štaka, Sonja Ristić, Miroslav Stefanović, Danilo Nikolić · 5 authors
Blockchain technology and smart contracts are central to decentralized applications. Operating on blockchain introduces challenges in design, development, and execution costs. On Ethereum, gas fees make optimization essential. This paper analyzes common mistakes affecting gas consumption and outlines strategies to improve efficiency. Using literature review and error systematization, key issues are identified and practical steps proposed. These recommendations, grounded in scientific research, aim to help developers design optimized and cost-effective smart contracts.
In the advancement of Industry 4.0, integrating intelligent systems, automation, and real-time data exchange has significantly transformed global industries. Among these developments, blockchain technology has emerged as a pivotal innovation, offering unparalleled data integrity, transparency, and decentralized control capabilities. This paper introduces a novel Ethereum-based decentralized application (DApp) architecture, comprising modular smart contracts to enhance industrial and societal systems, particularly within environmental sustainability in water body management. Each contract addresses a distinct operational layer, from secure storage and role-based access control to verified participation, drive coordination, and automated Ether-based reward distribution. The system was developed and tested in Remix IDE to validate functionality and integrity. This DApp framework secures workflows and extends blockchain utility to civic engagement through verified volunteer activities and incentive-based water conservation initiatives. Unlike prior work, this model integrates decentralized, scalable, and auditable mechanisms that have not previously been consolidated within a unified environmental DApp.
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.
Gas optimization is a critical concern in the development of Ethereum smart contracts, with substantial implications for both cost-efficiency and security. This review systematically examines the latest peer-reviewed research on gas consumption in Solidity contracts, focusing on how micro-level decisions such as function implementation, data member usage, and storage patterns as well as macro-level architectural choices, including object-oriented structures like aggregation and inheritance, influence gas usage. Empirical findings reveal that persistent storage operations and cross-contract calls represent the highest gas expenditures, while optimization techniques such as struct and variable packing, use of immutables, and minimized storage access can yield significant savings. Object-oriented features, although beneficial for modularity, tend to increase gas costs if not carefully managed. The adoption of formal verification frameworks ensures the correctness of automated optimizations and prevents the introduction of subtle bugs. Furthermore, network-level gas price volatility underlines the need for continuous benchmarking and adaptive strategies. Overall, the review demonstrates that effective gas optimization requires an integrated approach, combining empirical measurement, codelevel best practices, formal guarantees, and awareness of evolving network conditions.
This paper introduces a novel gradient-based framework for maintaining protocol invariants in decentralized finance (DeFi) systems, representing a fundamental departure from traditional reactive monitoring approaches. Rather than detecting violations after they occur and adjusting system perceptions, this framework implements a proactive closed-loop control system that influences external market dynamics through calibrated protocol actions. The core innovation lies in tracking confidence gradients—including velocity, acceleration, and momentum—to predict potential invariant violations before they materialize. The system employs a nine-parameter calibration vector that dynamically adjusts based on confidence trends, enabling the protocol to respond appropriately to increasing (healthy), decreasing (crisis), or stable market conditions. During crisis scenarios, aggressive parameter adjustments trigger protocol actions such as enhanced lender incentives and borrower penalties, directly influencing market participant behavior to maintain critical constraints like maximum lending rates. The framework establishes mathematical foundations for confidence gradient metrics, parameter constraint spaces, and crisis level assessment. It demonstrates how calibrated algorithmic behavior generates measurable influence on external actors, effectively changing market reality rather than merely observing it. Theoretical analysis proves bounded confidence oscillations and probabilistic invariant maintenance guarantees under the proposed calibration schemes. Practical implementation considerations include smart contract architecture, gas optimization strategies through batched updates and fixed-point arithmetic, and parameter discretization for on-chain deployment. A numerical crisis response example illustrates the system's ability to prevent rate violations through coordinated supply increases and demand reductions. The paper positions this approach as foundational for the Kera Protocol ecosystem, with applications extending beyond DeFi lending to automated market makers, stablecoin protocols, governance systems, and cross-chain bridges. This paradigm shift from observation to calibrated influence represents a significant advancement in blockchain protocol stability mechanisms.
Recently, Non-Fungible Tokens (NFTs) have attracted attention as valuable digital assets. However, NFT marketplaces face complex challenges in simultaneously recommending optimal pricing to sellers and desirable NFTs to buyers. Unlike conventional marketplaces that focus only on balancing demand and supply between sellers and buyers, these tasks are complicated by intricate value interdependencies arising from diverse buyer preferences, budgets, trait rarities, and the unprecedented breeding mechanisms. This paper formulates the NFT Project Pricing/Purchasing Recommendation (NP3R) problem, aiming to achieve a competitive equilibrium that concurrently optimizes seller revenue and buyer utility. We introduce BANTER, an iterative algorithm that jointly determines (1) optimal NFT purchases for buyers (via NFT-REC), considering breeding utility and current prices; and (2) optimal pricing for sellers (via PRICEREC), based on aggregated demand from NFT-REC. To efficiently manage the combinatorial complexity of breeding, we devise Optimal Parent Pair Selection (OPPS) and Heterogeneous Parent Set Selection (HPSS) schemes. Theoretical analysis guarantees BANTER to converge to a competitive equilibrium. Experiments on five real-world NFT datasets demonstrate its effectiveness in enhancing both seller revenue and average buyer utility. Source code: https://github.com/jimmy-academia/BANTER
A. Marques, Luiz Eduardo Terra de Faria, Diogo S. Mendonça
The exponential growth of the cryptoasset market and the advancement of decentralized technologies have challenged traditional models of tax collection. In particular, self-custody wallets, which allow users to maintain direct control over their digital assets without the mediation of financial institutions, pose significant obstacles to oversight and tax compliance. This paper proposes an approach for the automatic collection of taxes on foreign exchange operations with stablecoins, using smart contracts on decentralized exchanges (DEXs). Through the implementation of a Proof of Concept (PoC), based on the Split Payment logic, we demonstrate the technical feasibility of applying a tax rate, analogous to the IOF, directly during transactions carried out by self-custody wallets, without the need for prior user identification. Experimental results, validated on the Polygon mainnet, reinforce the potential of the proposed model as a practical solution aligned with the principles of Web3, contributing to the debate on automated tax compliance mechanisms in decentralized environments.
In decentralized governance, quadratic voting (QV)—where the cost of acquiring voting power is convex—optimally aggregates voter preferences, outperforming simpler linear voting (LV) mechanisms when voters have complete information. But what if they do not? We show that uncertainty not only breaks QV optimality but can also cause it to underperform LV. Intuitively, this is because cost convexity can disincentivize better-informed voters from adequately conveying their private information. The optimal mechanism varies with the distribution of stakes and information among voters, implying that QV’s known advantages in preference aggregation do not readily extend to common-value information aggregation settings. This paper was accepted by Will Cong for the Special Issue on the Digital Finance. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2024.08469 .
We present a declarative approach to on-chain limit order books (LOBs) that prioritizes formal verification over raw throughput. Unlike automated market makers, LOBs offer granular control and capital efficiency but are difficult to verify when implemented imperatively in Solidity. Using Pint, a declarative domain-specific language, we encode LOB matching logic, price-time priority, partial fills, and asset conservation, as first-order constraints. Off-chain solvers compute valid state transitions, while the blockchain performs lightweight constraint verification. We implement eight LOB predicates and evaluate performance using real-world transaction traces. Our declarative LOBs achieve 141 predicates/s for simple operations and 11 predicates/s for complex settlement with 1,000 accounts. Performance correlates strongly with state access patterns rather than constraint complexity. Critically, our approach eliminates verification challenges that make imperative smart contracts hard to formally verify, such as unbounded loops, recursion, cross-contract/function calls, and complex control flow. This enables correctness-by-construction through constraint satisfaction, removing the need to prove implementation conformance to specifications. This work demonstrates the first practical evidence that declarative LOBs achieve reasonable performance while providing superior verification guarantees for DeFi protocols.
Built environments face significant challenges in promoting material reuse due to the lack of trustworthy and transparent trading mechanisms. Existing digital platforms often fail to ensure fairness, bid confidentiality, and auditability. To address this gap, this paper presents the design and implementation of a verifiable auction system for trading reusable construction materials. Built on a Polkadot-based platform, the system supports sealed reverse auctions through a hybrid on-chain/off-chain architecture: encrypted and signed bids are stored in InterPlanetary File System (IPFS), while a Merkle root of valid bids is committed on-chain. Zero-knowledge proofs (ZKPs) enable verification of bid correctness without revealing bid values. Stress testing showed moderate latency from proof generation and IPFS operations, yet performance remained suitable for auctions lasting minutes or hours. The results demonstrate a scalable, privacy-preserving, and auditable auction mechanism that leverages decentralised technologies to advance circular economy goals.