The distribution of royalties associated with the exchange of digital assets, especially Non-Fungible Tokens (NFTs), is now more than ever a strong point of contention. Between conceptual disagreements and technical limitations, actors have implemented a variety of solutions tailored to their needs. In the process, creators and buyers have lost the possibility of transparent, trusted, and interoperable exchanges of said assets, often having to compromise to connect with the rest of the community. This study deals with the automatic distribution of royalty payments. We first investigate the current day limitations, and formally state their underlying requirements, before advancing a royalty-friendly NFT marketplace-agnostic trading framework. The advanced solution, referred to as the RM-TLSC–Royalty Management Token-LevelSmart Contract, establishes synergies between the token and Smart Contract paradigms, thus ensuring royalties are managed throughout the life cycle of the asset. A comprehensive, open-source software implementation is provided for the Ethereum blockchain, while the generality of the approach is cross-checked by an open-source proof of concept for the Tezos blockchain. The effectiveness of the results is illustrated through a case-study related to ISO 21000–23 Smart Contracts for Media standard.
Qinxu Ding, Weibiao Xu, Zhiguo Wang, David Kuo Chuen Lee
This paper aims to provide a comprehensive overview of the different voting schemes used in DAO governance. We will examine the various features of these schemes and compare their differences. We propose a new hypothetical voting mechanism specifically designed for decentralized and permissionless DAO governance. This new scheme, which incorporates incentive designs, is intended to be more efficient than existing schemes and can be easily adapted to a permissioned scenario. Through this examination and proposal, we hope to contribute to the ongoing discourse on how to govern decentralized autonomous organizations effectively.
Environmental externalities from cryptomining may be large, but have not been linked causally to mining incentives. We exploit daily variation in Bitcoin price as a natural experiment for an 86 megawatt coal-fired power plant with on-site cryptomining. We find that carbon emissions respond swiftly to mining incentives, with price elasticities of 0.69-0.71 in the short-run and 0.33-0.40 in the longer run. A $1 increase in Bitcoin price leads to $3.11-$6.79 in external damages from carbon emissions alone, well exceeding cryptomining's value added (using a $190 social cost of carbon, but ignoring increased local air pollution). As cryptomining requires ever more computing power to mine a given number of blocks, our study highlights both the revitalization of US fossil assets and the potential value of financial industry accounting standards that incorporate cryptomining externalities.
Ensuring Critical Infrastructure Resilience (CIR) hugely relies on decisions and actions made by networks of public and private stakeholders and their inter-organizational collaborative capabilities.Public-Private Collaborations (PPCs) are currently the most prominent approach for building CI resilience all around the world, but still face many obstacles and challenges.The Decentralized Autonomous Organization (DAO) paradigm, enabled by blockchain technology and smart contracts, provides the conceptual and technological means for new kinds of decentralized systems and allows for the emergence of new ways of governance and coordination for CIR.The paper explores the potential of DAO for enhancing governance, decision-making, and coordinated resource management in order to tackle the current challenges of cross-organizational collaboration in CIR.It does so by critically comparing the traditional multi-actor governance models and the innovative DAO governance approach, taking the main objectives of PPCs and their current challenges in CIR as conceptual lenses.The key aspects of network governance are discussed, along with the advantages/shortcomings of different approaches, and their implications in the context of PPCs for CIR.This explorative study paves the way for both new streams of theoretical research and blockchain pilot projects in real contexts.
Paul van Vulpen, H.M. Heijnen, Thijn Kroon, S. P. van Mens · 5 authors
Upgrading smart contracts allows DAOs and other Dapps to fix bugs and upgrade their functionality. The most widely used pattern for upgrading is the proxy pattern. However, the proxy pattern centralizes power in the one who has access to the admin address, which can be called admin centralization. In this article, we describe how the diamond pattern (ERC-2535) can be used to set up decentralized governance. We describe how the diamond pattern is configured and complemented by census governance. The proposed pattern has three advantages: 1) governance of smart contracts without admin centralization; 2) non-technical member participation in governance without smart contract knowledge; 3) user-friendly upgradeable DAO implementation using a graphical interface. To extend the use of the diamond pattern, we call for the creation of user-friendly tooling and smart contract facets.
The objective of this study is to determine the factors that contribute to market efficiency in the crypto-asset market. Despite prior evidence from the literature demonstrating variations in efficiency across assets and time, few have investigated driving factors beyond liquidity. By using a dataset of 122 crypto-assets with imbalanced data, our analysis discovers that both market conditions and inherent characteristics of crypto-assets significantly impact the predictability of their returns. Specifically, market efficiency is positively associated with increased liquidity and age. Our findings highlight that DAO projects demonstrate greater efficiency compared to non-DAO projects. This result suggests that transparent decentralized decision-making model can help reduce information asymmetry leading to a more efficient market pricing.
We study a mechanism design problem in the blockchain proof-of-stake (PoS) protocol. Our main objective is to extend the transaction fee mechanism (TFM) recently proposed in Chung and Shi (SODA, p.3856-3899, 2023), so as to incorporate a long-run utility model for the miner into the burning second-price auction mechanism $\texttt{BSP}(γ)$ proposed in Chung and Shi (where $γ$ is a key parameter in the strict $γ$-utility model that is applied to both miners and users). First, we derive an explicit functional form for the long-run utility of the miner using a martingale approach, and reveal a critical discontinuity of the utility function, namely a small deviation from being truthful will yield a discrete jump (up or down) in the miner's utility. We show that because of this discontinuity the $\texttt{BSP}(γ)$ mechanism will fail a key desired property in TFM, $c$-side contract proofness ($c$-SCP). As a remedy, we introduce another parameter $θ$, and propose a new $\texttt{BSP}(θ)$ mechanism, and prove that it satisfies all three desired properties of TFM: user- and miner-incentive compatibility (UIC and MIC) as well as $c$-SCP, provided the parameter $θ$ falls into a specific range, along with a proper tick size imposed on user bids.
Financial markets are undergoing an unprecedented transformation. Technological advances have brought major improvements to the operations of financial services. While these advances promote improved accessibility and convenience, traditional finance shortcomings like lack of transparency and moral hazard frictions continue to plague centralized platforms, imposing societal costs. In this paper, we argue how these shortcomings and frictions are being mitigated by the decentralized finance (DeFi) ecosystem. We delve into the workings of smart contracts, the backbone of DeFi transactions, with an emphasis on those underpinning token exchange and lending services. We highlight the pros and cons of the novel form of decentralized governance introduced via the ownership of governance tokens. Despite its potential, the current DeFi infrastructure introduces operational risks to users, which we segment into five primary categories: consensus mechanisms, protocol, oracle, frontrunning, and systemic risks. We conclude by emphasizing the need for future research to focus on the scalability of existing blockchains, the improved design and interoperability of DeFi protocols, and the rigorous auditing of smart contracts.
Blockchain smart contracts can support the decentralisation of business processes, but due to smart contracts’ specifics, their development is a complicated process. Introducing model-driven development principles in smart contract development can facilitate requirement specification, design, and implementation activities. This paper presents a model-driven development method MDAsmartCD (Model-Driven Architecture-based Smart Contract Development) to alleviate smart contract development by supporting the complete MDA life cycle, covering the definition of Computation-Independent Model, Platform-Independent Model, and two instances of Platform-Specific Models. In MDAsmartCD, model transformations (model-to-model and model-to-text) are used to produce smart contract code in the Hyperledger Fabric platform Go and the Ethereum platform Solidity programming languages. The method application was demonstrated by implementing the smart contract for the hackathon solution and executing the generated Solidity and Go smart contracts in the workflow of issuing certificates for hackathon participants. During the execution of the workflow, both deployed smart contracts behaved identically and recorded analogous results in respective blockchain data storages. This demonstrated that the MDAsmartCD method enables the generation of compilable and executable smart contract code, ready for deployment on a blockchain platform.
This paper examines the economic mechanism of cryptocurrency mining. By presenting a profit function, a maximization equilibrium is obtained. The model provides a formal approach to the demand for hashing power as a function of revenues, mining costs and the number of miners. We consider how the equilibrium is affected by passive miners. We use these results to introduce a formulation of the price elasticity of the demand for hashing power with respect to the cost of energy. The model is simulated using Reinforcement Learning algorithms that arrive to similar equilibrium results. The article concludes with implications of the model for policymaking.
Decentralized finance (DeFi) is by far the most popular application of blockchain technology. Despite the wide acceptance of new financial instruments and services, there are still many unexplored areas in the field. We dedicate this research to the understanding of one of the most crucial limitations of decentralized finance-oracles. DeFi protocols, as well as other blockchain applications, function in a closed environment and regularly need to fetch real-world information (e.g., assets' prices)-the tool used for this purpose is called an oracle. We review the existing oracle types in DeFi applications and focus our research on the least explored one: when another protocol, typically a decentralized exchange, serves as a price oracle. After explaining the mechanisms behind the decentralized exchanges, we introduce an algorithmic model that allows one to safely design a decentralized oracle and adjust crucial parameters. We believe that understanding and implementing the logic presented in the model can help to reduce the chances of price manipulations attacks, which are the most frequent incident types in DeFi.
Mathematical ranking plays a critical role in the era of the internet and bigdata. Google's PageRank is well-known as a trillion-dollar algorithm. Definitely, algorithmic ranking frameworks are found on every search engine. In this paper, the article shall investigate how PageRank can be applied in the blockchain space to build up reliable and verifiable social credit and reputation systems. It is expected to provide a measure of credibility complementary and parallel with FICO, which is not applicable for individuals lacking credit information in financial institutions. Moreover, the approach proposes an unbiased method of interpreting and measuring real social interaction and reputation ranking on a blockchain network. The authors envision a future of payment based on cryptocurrencies (especially stable coins) and digital fiats; thus the proposed credit scoring framework shall be helpful for P2P credit and lending networks, possibly for decentralized finance (Defi) applications.
As a distributed ledger technology, blockchain can be used in the fields of information sharing, logistics chain, certificate storage and anti-counterfeiting. However, due to the isolated nature of the blockchain network and the high degree of heterogeneity between chains, the connection between different chains is hindered, which makes each blockchain form a value island and cannot serve the practical applications well. The emergence of cross chain technology realizes the value circulation between different chains and enhances the interoperability and scalability of blockchains. Among them, the cross-chain technology of notary mechanism transforms the trust problem among cross-chain users into the loyalty problem of notary, and is favored for its ability to support different types of underlying blockchain systems in a more flexible manner. However, the introduction of notaries in the notary mechanism also leads to the risk of centralization, and the loyalty of notaries will directly determine the success of cross-chain transactions. In this paper, by introducing the improved PageRank algorithm, we design a dynamic notary group election mechanism based on reputation value, which effectively avoids malicious nodes from becoming notaries and improves the success rate of cross-chain transactions while preventing the over-concentration of rights in a single node. The experimental analysis shows that selecting notary representatives by dynamically adjusting the reputation value ranking of notary nodes increases the selection probability of loyal nodes, which is more reasonable than the method of randomly selecting notaries.
Transaction fee markets are essential components of blockchain economies, as they resolve the inherent scarcity in the number of transactions that can be added to each block. In early blockchain protocols, this scarcity was resolved through a first-price auction in which users were forced to guess appropriate bids from recent blockchain data. Ethereum's EIP-1559 fee market reform streamlines this process through the use of a base fee that is increased (or decreased) whenever a block exceeds (or fails to meet) a specified target block size. Previous work has found that the EIP-1559 mechanism may lead to a base fee process that is inherently chaotic, in which case the base fee does not converge to a fixed point even under ideal conditions. However, the impact of this chaotic behavior on the fee market's main design goal -- blocks whose long-term average size equals the target -- has not previously been explored. As our main contribution, we derive near-optimal upper and lower bounds for the time-average block size in the EIP-1559 mechanism despite its possibly chaotic evolution. Our lower bound is equal to the target utilization level whereas our upper bound is approximately 6% higher than optimal. Empirical evidence is shown in great agreement with these theoretical predictions. Specifically, the historical average was approximately 2.9% larger than the target rage under Proof-of-Work and decreased to approximately 2.0% after Ethereum's transition to Proof-of-Stake. We also find that an approximate version of EIP-1559 achieves optimality even in the absence of convergence.
Jiaqi Wang, Ning Lu, Ziyang Gong, Wenbo Shi · 5 authors
With the arrival of the 5G era, wireless communication technologies and services are rapidly exhausting the limited spectrum resources. Spectrum auctions came into being, which can effectively utilize spectrum resources. Because of the complexity of the electronic spectrum auction network environment, the security of spectrum auction can not be guaranteed. Most scholars focus on researching the security of the single-sided auctions, while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and buyers. Researchers begin to design the secure double spectrum auction mechanisms, in which two semi-honest agents are introduced to finish the spectrum auction rules. But these two agents may collude with each other or be bribed by buyers and sellers, which may create security risks, therefore, a secure double spectrum auction is proposed in this paper. Unlike traditional secure double spectrum auctions, the spectrum auction server with Software Guard Extensions (SGX) component is used in this paper, which is an Ethereum blockchain platform that performs spectrum auctions. A secure double spectrum protocol is also designed, using SGX technology and cryptographic tools such as Paillier cryptosystem, stealth address technology and one-time ring signatures to well protect the private information of spectrum auctions. In addition, the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification, and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum auctions. Finally, security analysis and performance evaluation of our protocol are discussed.
Alexis Asseman, Tomasz Kornuta, Patel, Anirudh, Matt Deible · 5 authors
The Graph Protocol indexes historical blockchain transaction data and makes it available for querying. As the protocol is decentralized, there are many independent Indexers that index and compete with each other for serving queries to the Consumers. One dimension along which Indexers compete is pricing. In this paper, we propose a bandit-based algorithm for maximization of Indexers' revenue via Consumer budget discovery. We present the design and the considerations we had to make for a dynamic pricing algorithm being used by multiple agents simultaneously. We discuss the results achieved by our dynamic pricing bandits both in simulation and deployed into production on one of the Indexers operating on Ethereum. We have open-sourced both the simulation framework and tools we created, which other Indexers have since started to adapt into their own workflows.
Online data trading has grown alongside the ever-increasing use of digital services. Industries are accruing the benefits of this data access to perform mission-critical tasks by analyzing available data for greater insight. Unsurprisingly, data trading has not focused on improved data seller protection with preferences and controls. The objective of this paper is to explore the enforcement of seller preferences within smart contracts using blockchain technology. Data trading is only possible when a buyer satisfies the conditions predefined by the seller. Geographic location, type or size of buyer's company are some examples of seller preferences. A preferences algorithm provides an automated contract between seller and buyer without the involvement of any broker or third party. Hybrid simulation (HS) methods are used to test and evaluate the viability of our novel data control approach.
Sen Yang, Fan Zhang, Ken Huang, Xi Chen · 6 authors
Blockchains offer strong security guarantees, but they cannot protect the ordering of transactions. Powerful players, such as miners, sequencers, and sophisticated bots, can reap significant profits by selectively including, excluding, or re-ordering user transactions. Such profits are called Miner/Maximal Extractable Value or MEV. MEV bears profound implications for blockchain security and decentralization. While numerous countermeasures have been proposed, there is no agreement on the best solution. Moreover, solutions developed in academic literature differ quite drastically from what is widely adopted by practitioners. For these reasons, this paper systematizes the knowledge of the theory and practice of MEV countermeasures. The contribution is twofold. First, we present a comprehensive taxonomy of 30 proposed MEV countermeasures, covering four different technical directions. Secondly, we empirically studied the most popular MEV-auction-based solution with rich blockchain and mempool data. We also present the Mempool Guru system, a public service system that collects, persists, and analyzes the Ethereum mempool data for research. In addition to gaining insights into MEV auction platforms' real-world operations, our study shed light on the prevalent censorship by MEV auction platforms as a result of the recent OFAC sanction, and its implication on blockchain properties.
Mohak Goyal, Geoffrey Ramseyer, Ashish Goel, David Mazières
Constant Function Market Makers (CFMMs) are a tool for creating exchange markets, have been deployed effectively in prediction markets, and are now especially prominent in the Decentralized Finance ecosystem. We show that for any set of beliefs about future asset prices, an optimal CFMM trading function exists that maximizes the fraction of trades that a CFMM can settle. We formulate a convex program to compute this optimal trading function. This program, therefore, gives a tractable framework for market-makers to compile their belief function on the future prices of the underlying assets into the trading function of a maximally capital-efficient CFMM. Our convex optimization framework further extends to capture the tradeoffs between fee revenue, arbitrage loss, and opportunity costs of liquidity providers. Analyzing the program shows how the consideration of profit and loss leads to a qualitatively different optimal trading function. Our model additionally explains the diversity of CFMM designs that appear in practice. We show that careful analysis of our convex program enables inference of a market-maker's beliefs about future asset prices, and show that these beliefs mirror the folklore intuition for several widely used CFMMs. Developing the program requires a new notion of the liquidity of a CFMM, and the core technical challenge is in the analysis of the KKT conditions of an optimization over an infinite-dimensional Banach space.
Philippe Bergault, Louis Bertucci, David Bouba, Olivier Guéant
With the emergence of decentralized finance, new trading mechanisms called Automated Market Makers have appeared. The most popular Automated Market Makers are Constant Function Market Makers. They have been studied both theoretically and empirically. In particular, the concept of impermanent loss has emerged and explains part of the profit and loss of liquidity providers in Constant Function Market Makers. In this paper, we propose another mechanism in which price discovery does not solely rely on liquidity takers but also on an external exchange rate or price oracle. We also propose to compare the different mechanisms from the point of view of liquidity providers by using a mean / variance analysis of their profit and loss compared to that of agents holding assets outside of Automated Market Makers. In particular, inspired by Markowitz' modern portfolio theory, we manage to obtain an efficient frontier for the performance of liquidity providers in the idealized case of a perfect oracle. Beyond that idealized case, we show that even when the oracle is lagged and in the presence of adverse selection by liquidity takers and systematic arbitrageurs, optimized oracle-based mechanisms perform better than popular Constant Function Market Makers.
Contract management has always been a classic task for companies; the management of vendors to the remittance handling goes in a cycle, requiring constant monitoring and risk assessment. The vendor-related frauds account for a huge amount of money. It is expected that the fraud detection and prevention market is expected to reach 63.5 billion USD worldwide by 2023, with a CAGR of 26.6%. Hence, companies are looking for a unified solution that can track the phases in a traditional contract lifecycle so the escrow charges can be reduced and centralized monitoring is possible. This paper has presented how a traditional contract life cycle happens, a comparison between traditional contract and smart contract, how a smart contract functions, and its underlying technology. High-level documents like architecture diagrams should be designed in this phase. An architecture diagram depicts business logic in a pictorial format; it also helps developers to follow the correct path during the development. We have also presented the current business challenges in implementing smart contracts and the future scope and further applications.
Decentralized Autonomous Organization (DAO) is an organization constructed by automatically executed rules such as via smart contracts, holding features of the permissionless committee, transparent proposals, and fair contribution by stakeholders. As of Nov 2022, DAO has impacted over \$11.2B market caps. However, there are no substantial studies focused on this emerging field. To fill the gap, we start from the ground truth by empirically studying the breadth and depth of the DAO markets in mainstream public chain ecosystems in this paper. We dive into the most widely adoptable DAO launchpad, \textit{Snapshot}, which covers 95\% in the wild DAO projects for data collection and analysis. By integrating extensive enrolled DAOs and corresponding data measurements, we explore statistical data from Snapshot and try to demystify its undiscovered truths by delivering a series of summarised insights. We also present DAO status, patterns, distribution, and trends. To our knowledge, this is the first empirical study putting concentration on DAO spaces.