Abstract: Smart contracts are self-executing, deterministic scripts that run transparently on top of a blockchain. They enable trusted transactions and agreements between anonymous parties without the need for a trusted figure or authority. The smart contract code and agreement between the parties are publicly available on the blockchain, making transactions transparent, traceable, and irreversible. Smart contracts have the potential to revolutionize and disrupt numerous industries' traditional operating procedures. Although research on smart contracts has yielded significant results, their full potential remains untapped. A bibliometric analysis was performed in this paper to obtain a holistic overview and to assist academic researchers in developing a comprehensive understanding of the state of scientific research on smart contracts. 513 articles on smart contracts were extracted and analyzed using biblioshiny and VOSviewer from the core collection of the Web of Science (WOS) database. Influential journals, top authors, most contributing countries, and impactful articles in the smart contract domain are revealed. A three-fields plot is constructed to show the interactions between the most relevant sources, author key words, and countries, providing a deeper understanding of the state of global research on smart contracts. Furthermore, keyword co-occurrence analysis identified four clusters representing underlying research streams: (1) smart contracts technology and its applications in healthcare (2) applications of smart contracts in supply chain management (3) smart contracts for the Internet of Things (IOT) (4) Smart contracts for business ventures on consortium blockchains Finally, future research directions are suggested based on areas of low coverage but high potential impact
Governance in blockchain platforms is an increasingly important topic. A particular concern related to voting procedures is the formation of dominant positions, which may discourage participation of minorities. A main feature of standard majority voting is that individuals can indicate their preferences but cannot express the intensity of their preferences. This could sometimes be a drawback for minorities who may not have the opportunity to obtain their most desirable outcomes, even when such outcomes are particularly important for them. For this reason a voting method, which in recent years gained visibility, is quadratic voting (QV), which allows voters to manifest both their preferences and the associated intensity. In voting rounds, where in each round users express their preference over binary alternatives, what characterizes QV is that the sum of the squares of the votes allocated by individuals to each round has to be equal to the total number, budget, of available votes. That is, the cost associated with a number of votes is given by the square of that number, hence it increases quadratically. In the paper, we discuss QV in proof-of-stake-based blockchain platforms, where a user’s monetary stake also represents the budget of votes available in a voting session. Considering the stake as given, the work focuses mostly on a game theoretic approach to determine the optimal allocation of votes across the rounds. We also investigate the possibility of the so-called Sybil attacks and discuss how simultaneous versus sequential staking can affect the voting outcomes with QV.
We are often faced with the non-trivial task of designing incentive mechanisms in the era of Web3. As history has shown, many Web3 services failed mostly due to the lack of a rigorous incentive mechanism design based on token economics. However, traditional mechanism design, where there is an assumption that the users of services strategically make decisions so that their expected profits are maximized, often does not capture their real behavior well as it ignores humans' psychological bias in making decisions under uncertainty. In this paper, we propose an incentive mechanism design for crypto-enabled services using behavioral economics. Specifically, we take an example of a crypto lottery game in this work and incorporate a seminal work of cumulative prospect theory into its lottery game mechanism (or rule) design. We designed four mechanisms and compared them in terms of utility, a metric of how appealing a mechanism is to participants, and a game operator's expected profit. Our approach is generic and will be applicable to a wide range of crypto-based services where a decision has to be made under uncertainty.
Alyssa Blackburn, Christoph Huber, Yossi Eliaz, Muhammad Shahzads Shamim · 9 authors
Bitcoin is a digital currency designed to rely on a decentralized, trustless network of anonymous agents. Using a pseudonymous-address-linking procedure that achieves >99% sensitivity and >99% specificity, we reveal that between launch (January 3rd, 2009), and when the price reached $1 (February 9th, 2011), most bitcoin was mined by only sixty-four agents. This was due to the rapid emergence of Pareto distributions in bitcoin income, producing such extensive resource centralization that almost all contemporary bitcoin addresses can be connected to these top agents by a chain of six transactions. Centralization created a social dilemma. Attackers could routinely exploit bitcoin via a "51% attack", making it possible for them to repeatedly spend the same bitcoins. Yet doing so would harm the community. Strikingly, we find that potential attackers always chose to cooperate instead. We model this dilemma using an N-player Centipede game in which anonymous players can choose to exploit, and thereby undermine, an appreciating good. Combining theory and economic experiments, we show that, even when individual payoffs are unchanged, cooperation is more frequent when the game is played by an anonymous group. Although bitcoin was designed to rely on a decentralized, trustless network of anonymous agents, its early success rested instead on cooperation among a small group of altruistic founders.
This dissertation is composed of two main research projects. The first, which was conducted with my adviser Xiaoming Song as a continuation of her work with with her previous student Nathan Anderson-Stahl. In that chapter, we consider a class of general backward stochastic differential equations and backward doubly stochastic differential equations to provide a standard method to prove the existence and uniqueness of the Lp solutions and to obtain the Lp estimates for the solutions. The other project was conducted in collaboration with Josh McGinnis and corresponds to the second chapter in which we provide a physical zero knowledge proof for the popular app game Flow Free. We then show that the methodology can be extended to provide zero knowledge proofs for the related graph problems of the paired many-to-many disjoint covering path problem, the unpaired many-to-many disjoint covering path problem and Hamiltonian cycles.
Smart contracts constitute the foundation for blockchain distributed applications. These constructs enable transactions in trustless environments using consensus algorithms and software-controlled verification rules. In the current state of the art, there is a shortage of works on the adaptability of smart contracts, and the re-use of their source code is limited mainly to cloning. The paper discusses the pattern of smart contract design and implementation with the overt declaration of verification rules. The author introduces two advantages of the pattern: Firstly, run-time reconfigurability of the list of smart contract verification rules to adjust for various transaction types. Secondly, the re-use of verification rules between different configurations of the smart contract, and among diverse smart contracts. The paper uses blockchain platform-independent stereotypes from a dedicated Unified Modeling Language (UML) profile for designing smart contracts and verification rules. The implementation of the pattern is developed in object-oriented Java language. The pattern exploits polymorphism and controls inheritance by using sealed classes with permission for specialization only for selected final ones. Thus, the pattern ensures two recently highly desired properties in smart contract design and development: re-use and security. Moreover, the declared verification rules list facilitates test automation and reduces test preparation effort due to the re-use of test classes among smart contract configurations. The pattern usage is illustrated in the example of renewable energy exchange within the prosumers community and amid various communities.
Giovanni De Gasperis, Sante Dino Facchini, Alessio Susco
Tax credit stimulus and fiscal bonuses had a very important impact on Italian economy in the last decade. Along with a huge expansion in constructions a relevant increase in scams and frauds has come too. The aim of this article is to design a possible system to track and control the whole tax credit process from its generation to its redeem through a Decentralized Autonomous Organization architecture enriched with a Multi Agent Systems to implement controllers.
Blockchain technology spread very quickly during the last few years and has become one of the most popular trends among the research and developers community. In particular, the Ethereum blockchain is one of the most supported and used for developing smart contracts, which are informatics protocols that provide a higher level of security than traditional contracts and reduce other transaction costs associated with the bargaining practice. Nowadays, the transaction number associated with smart contracts deploying increased widely, and it is difficult for researchers and developers to keep track of programming trends. This work proposes a dataset containing only specific categories of smart contracts associated with the most popular trends of the last five years. Mainly, the proposed collection of programs contains Token and Non-Fungible-Token programs, whose popularity has increased a lot since their first appearance on the blockchain.
Lioba Heimbach, Eric Schertenleib, Roger Wattenhofer
Trade execution on Decentralized Exchanges (DEXes) is automatic and does not require individual buy and sell orders to be matched. Instead, liquidity aggregated in pools from individual liquidity providers enables trading between cryptocurrencies. The largest DEX measured by trading volume, Uniswap V3, promises a DEX design optimized for capital efficiency. However, Uniswap V3 requires far more decisions from liquidity providers than previous DEX designs. In this work, we develop a theoretical model to illustrate the choices faced by Uniswap V3 liquidity providers and their implications. Our model suggests that providing liquidity on Uniswap V3 is highly complex and requires many considerations from a user. Our supporting data analysis of the risks and returns of real Uniswap V3 liquidity providers underlines that liquidity providing in Uniswap V3 is incredibly complicated, and performances can vary wildly. While there are simple and profitable strategies for liquidity providers in liquidity pools characterized by negligible price volatilities, these strategies only yield modest returns. Instead, significant returns can only be obtained by accepting increased financial risks and at the cost of active management. Thus, providing liquidity has become a game reserved for sophisticated players with the introduction of Uniswap V3, where retail traders do not stand a chance.
Parking problem has become a bottle neck of urban traffic management. On one hand, there is no effective way to get timely information of available parking lots. On the other hand, owners of private parking spaces are less willing to share their spare lots. To deal with the parking problem, a new parking sharing network named ParkChain is firstly proposed using blockchain to build a decentralized but trustworthy network. Herein, ParkChain provides a distributed autonomous infrastructure for both vehicle drivers and park granters, which can promote the extensive parking resource sharing and relieve the parking problem. A new blockchain consensus protocol named Proof-of-Planned-Behavior (PoPB) is proposed. It builds the model of the autonomous consensus process based on the theory of planned behavior (TPB), derives a computable threshold for qualification of block data authorizers, and then develops a dynamic authorizer group mechanism for creditability and decentrality considerations. Furthermore, various smart contracts are developed to carry out the parking services transparently. Finally, the prototype has been successfully implemented in a university campus setting to demonstrate the effectiveness of ParkChain.
Many implementations of smart contracts available in NFT marketplaces today allow the modification of NFT token attributes, without any specific mechanism to control the consistency with off-chain metadata. We believe this is a weakness in overall design of NFTs today. We propose a computation model called the Asset Proxy NFT that guarantees the consistency between the NFT token (on-chain) and its corresponding asset metadata (off-chain). In general, the proposed model can be applied to any type of NFT that requires immutability or controlled mutability of metadata. A second contribution of this paper is the notion of the NFT design patterns which recognizes that a coherent framework for dealing with hybrid assets is required, and that for specific hybrid-asset deployments, suitable technological components must be utilized under the framework.
Open Innovation (OI) models have been studied in many fields. However, the challenges and opportunities of a possible OI paradigm application in external auditing have been under-researched. Recent corporate scandals are currently triggering changes and improvements in the regulatory framework by targeting, in particular, the dominance of the so-called “Big Four”. The main research question is whether a permissioned blockchain ecosystem could better enhance an OI paradigm and prove more suitable than the Semi-Open Innovation (SOI) paradigm that currently shapes the external audit field. Some challenges are considered in this article. Notably, blockchain requires suitable legal frameworks to ensure legally binding transactions. Moreover, multidisciplinary teams and high investments are required to develop efficient blockchain ecosystems and exploit the power of data analytics. Systematic analysis is performed based on a relevant literature review, along with abductive reasoning and applied modelling methodologies. The analyses demonstrate that the current Semi-Open Innovation external audit model is inefficient because it has led to market concentration, conflicting interests, and even fraud. Therefore, the regulators’ role in promoting fully Open Innovation models in the audit industry is essential to ensure transparency, information sharing, fair competition, innovation, and collaboration among audit professionals. Hence, this research aims at providing a different perspective by focusing on the necessary assumptions needed to ensure successful application of technologies in the audit field. The innovative introduction of a permissioned blockchain-based audit system is also suggested to ensure the feasibility of the shift from Semi-Open to Open Innovation.
Rabia Musheer Aziz, Mohammed Farhan Baluch, Sarthak Patel, Pavan Kumar
Ethereum smart contracts have recently received new commercial applications and a lot of attention from the scientific community. Ethereum eliminates the requirement for a trusted third party by allowing untrusted parties to expose contract details in computer code. Nonetheless, as online commerce grows, plenty of fraudulent activities, such as money laundering, bribery, and phishing, emerge as major threats to trade security. For correctly recognizing fraudulent transactions, this paper developed a Light Gradient Boosting Machine (LGBM) technique-based model. The modified LGBM model optimized the parameters of Light GBM using the Euclidean distant structured estimation approach. This paper also examines the performance of different popular models such as Random Forest (RF), Multi-Layer Perceptron (MLP), Logistic Regression, k-Nearest Neighbors (KNN), XGBoost, Support Vector Classification (SVC), and ADAboost with limited features and compares their performance metrics with the proposed model for Ethereum fraudulent activity classification. A comparative performance evaluation matrices scores of different popular models along with the proposed model demonstrated the applicability of the proposed approach. The modified LGBM algorithms and RF models demonstrate the best performance compared to other models with the highest accuracies, while the modified LGBM algorithm has a slightly superior performance of 99.17 percent compared to the RF model's 98.26 percent.
We quantify Non Fungible Token (NFT) rarity and investigate how it impacts market behaviour by analysing a dataset of 3.7M transactions collected between January 2018 and June 2022, involving 1.4M NFTs distributed across 410 collections. First, we consider the rarity of an NFT based on the set of human-readable attributes it possesses and show that most collections present heterogeneous rarity patterns, with few rare NFTs and a large number of more common ones. Then, we analyze market performance and show that, on average, rarer NFTs: (i) sell for higher prices, (ii) are traded less frequently, (iii) guarantee higher returns on investment (ROIs), and (iv) are less risky, i.e., less prone to yield negative returns. We anticipate that these findings will be of interest to researchers as well as NFT creators, collectors, and traders.
Enrico Tedeschi, Tor-Arne S. Nordmo, Dag Johansen, Håvard D. Johansen
The transaction-rate bottleneck built into popular proof-of-work (PoW)-based cryptocurrencies, like Bitcoin and Ethereum, leads to fee markets where transactions are included according to a first-price auction for block space. Many attempts have been made to adjust and predict the fee volatility, but even well-formed transactions sometimes experience unexpected delays and evictions unless a substantial fee is offered. In this article, we propose a novel transaction inclusion model that describes the mechanisms and patterns governing miners decisions to include individual transactions in the Bitcoin system. Using this model we devise a Machine Learning (ML) approach to predict transaction inclusion. We evaluate our predictions method using historical observations of the Bitcoin network from a five month period that includes more than 30 million transactions and 120 million entries. We find that our Machine Learning (ML) model can predict fee volatility with an accuracy of up to 91%. Our findings enable Bitcoin users to improve their fee expenses and the approval time for their transactions.
Ankit Bansal, Osman Y. Özaltın, Reha Uzsoy, Karl G. Kempf
Abstract Product transitions involve the replacement of products currently being produced and distributed by a firm with new products throughout the firm's supply chain. In high technology industries effective management of product transitions is crucial to long‐term success, and involves the coordination of multiple product development units and a manufacturing unit by a product division serving a particular market. Since the different units are organizationally autonomous, and the product division does not have access to their detailed technological constraints and internal operating policies, a decentralized solution is required. We develop a price‐based coordination framework using the subadditive dual of a mixed‐integer linear program that seeks to maximize the number of units whose proposed plans are included in the final solution. The proposed approach yields superior solutions to a linear‐programming‐based branch‐and‐price approach within the same computing budget. We discuss the broader applicability of this integer column generation approach, and suggest directions for future work.
Ingrid Bauer, José Parra-Moyano, Karl Schmedders, Gerhard Schwabe
Markets in which similar goods of different qualities are sold suffer from information asymmetries and their negative consequences. Dealers have established themselves, and mediate these markets through their use of quality signals. While these signals help to mitigate information asymmetries, these markets still function well below their optimum: a large share of goods sold are overpriced, and most of the benefits are reaped by intermediaries. In this paper we build on prior research that proposes the use of blockchain as an enabler for trusted, decentralized asset documentation. Applying a socio-technical lens, we describe how blockchain-enabled multi-party certification affords dealers the action potential to send signals that are more closely correlated to the unobservable quality of the underlying good (i.e., signals with a higher fit) than the signals they send today. We then both theorize and experimentally explore the market effects of the two types of signals. Using data from a laboratory market experiment with 210 participants, we find empirical evidence that multi-party certification affords dealers the action potential to send signals of significantly higher fit than those sent by intermediaries alone, leading to a reduction in information asymmetries, a more efficient allocation of goods, and an increase in market fairness.
We empirically study the state of three prominent DAO governance systems on the Ethereum blockchain: Compound, Uniswap and ENS. In particular, we examine how the voting power is distributed in these systems. Using a comprehensive dataset of all governance token holders, delegates, proposals and votes, we analyze who holds the voting power and how this power is being used to influence governance decisions. While we reveal that the majority of voting power is concentrated in the hands of a small number of addresses, we rarely observe these powerful entities overturning a vote by choosing a different outcome than that of the overall community and less influential voters.
Decentralized Autonomous Organization (DAO) is very popular in Decentralized Finance (DeFi) applications as it provides a decentralized governance solution through blockchain. We analyze the governance characteristics in the Maker protocol, its stablecoin DAI and governance token Maker (MKR). To achieve that, we establish several measurements of centralized governance. Our empirical analysis investigates the effect of centralized governance over a series of factors related to MKR and DAI, such as financial, transaction, network and twitter sentiment indicators. Our results show that governance centralization influences both the Maker protocol, and the distribution of voting power matters. The main implication of this study is that centralized governance in MakerDAO very much exists, while DeFi investors face a trade-off between decentralization and performance of a DeFi protocol. This further contributes to the contemporary debate on whether DeFi can be truly decentralized. centralized governance in MakerDAO very much exists, while DeFi investors face a trade-off between efficiency and decentralization. This further contributes to the contemporary debate on whether DeFi can be truly decentralized.
Zhou Liao, Shuwei Song, Hang Zhu, Xiapu Luo · 10 authors
Being the most popular programming language for developing Ethereum smart contracts, Solidity allows using inline assembly to gain fine-grained control. Although many empirical studies on smart contracts have been conducted, to the best of our knowledge, none has examined inline assembly in smart contracts. To fill the gap, in this paper, we conduct the first large-scale empirical study of inline assembly on more than 7.6 million open-source Ethereum smart contracts from three aspects, namely, source code, bytecode, and transactions after designing new approaches to tackle several technical challenges. Through a thorough quantitative and qualitative analysis of the collected data, we obtain many new observations and insights. Moreover, by conducting a questionnaire survey on using inline assembly in smart contracts, we draw new insights from the valuable feedback. This work sheds light on the development of smart contracts as well as the evolution of Solidity and its compilers.
Damián Emilio Gibaja Romero, Rosa María Cantón Croda
The execution of smart contracts (SCs) relies on consensus algorithms that validate the miner who executes the contract and gets a fee to cover her expenditure. In this sense, miners are strategic agents who may focus on executing those contracts with the largest fee, to the detriment of other SCs’ execution times, which also harms the blockchain’s reputation. This paper analyzes the impact of miners’ competition on SCs’ execution times in a public blockchain. First, we explain that the Proof-of-Work mechanism casts similarities with a time auction, where the one who first adds blocks is the one who executes the contract and gets the fee. At equilibrium, costs negatively affect execution times, while the opposite holds concerning fees. However, this result does not capture the competition for other contracts; hence, we apply the Naïve Bayes method to classify SCs by considering a simulated database that comprises miners’ competition for several contracts. We observe that simultaneous competition generates patterns that differ from the ones expected by the auction solution. For example, miners’ valuation does not accelerate contracts’ execution, and high-cost smart contracts do not necessarily execute at last places.
Internet backboned crowdsourcing utilizes network-wide resources to solve complicated and large-scale tasks, which are not accomplishable for independent individuals. Existing crowdsourcing platforms are mostly centralized solutions with reliability and trustworthiness fragile to single-point failures on the central servers. The innovation of distributed ledgers as blockchain inspires us to optimize the traditional crowdsourcing procedure with distributed sustainability. We propose a blockchain-based design of the distributed secure crowdsourcing scheme for task distribution and result verification without relying on any third trusted institution. A preference-based task distribution (PTD) mechanism is presented which guarantees the percentage of task distribution and the satisfaction of the chosen workers. Task works are continuously assessed for reputations based on their historical behaviors. Task completion correctness is verified by blockchain consensus in two different scenarios after workers submit their results with reputations. We implement a prototype system based on the Ethereum chain with PTD and solution verification components. With various tasks and scenarios evaluated in the system, the proposed distributed crowdsourcing framework shows system reliability, data security, and scenario feasibility.
Matthias Lohr, Kenneth Skiba, Marco Konersmann, Jan Jürjens · 5 authors
Existing fair exchange protocols usually neglect consideration of cost when\nassessing their fairness. However, in an environment with non-negligible\ntransaction cost, e.g., public blockchains, high or unexpected transaction cost\nmight be an obstacle for wide-spread adoption of fair exchange protocols in\nbusiness applications. For example, as of 2021-12-17, the initialization of the\nFairSwap protocol on the Ethereum blockchain requires the selling party to pay\na fee of approx. 349.20 USD per exchange. We address this issue by defining\ncost fairness, which can be used to assess two-party exchange protocols\nincluding implied transaction cost. We show that in an environment with\nnon-negligible transaction cost where one party has to initialize the exchange\nprotocol and the other party can leave the exchange at any time cost fairness\ncannot be achieved.\n
Hans Gersbach, Akaki Mamageishvili, Manvir Schneider
On several proof-of-stake blockchains, agents engaged in validating transactions can open a pool to which others can delegate their stake in order to earn higher returns. We develop a model of staking pool formation in the presence of malicious agents and establish existence and uniqueness of equilibria. We then identify potential and risk of staking pools. First, allowing for staking pools lowers blockchain security. Yet, honest stake holders obtain higher returns. Second, by choosing welfare optimal distribution rewards, staking pools prevent that malicious agents receive large rewards. Third, when pool owners can freely distribute the returns from validation to delegators, staking pools disrupt blockchain operations, since malicious agents attract most delegators by offering generous returns.