With the exception of some well-funded industries, legal documents remain difficult and expensive to use, and prone to ambiguities. Emerging blockchain technologies hold the promise of changing this, however the tools for coding these 'smart contracts' require programmers and are prone to fraud. To fully realise the benefits of smart contracts, widespread adoption is required, which depends on improving security and replacing programmers with tools that lawyers, business-people and the general public can use. Our objective is to investigate improved approaches to the creation, testing and deployment of smart contracts by demonstrating that pure declarative languages can be used, and that these facilitate achieving improved utility in smart contracts. Our investigation implemented a 'Will and Testament' as a smart contract on a custom simulator, and demonstrated improved utility by auto-generating a smart contract from a status-quo user interface with an untrained user. We found a number of small benefits to using a declarative language like simplification, ease of code auto-generation and ease of testing. We have identified an approach to smart contract creation supportive of adoption because conversion starts with current legal contacts, is tolerant of varying levels of automation, and allows human-in-the-loop interaction. Smart contracts are seen as game changing by many, and should issues with cost, usability and security be solved, the economic impact is likely to be large.
Zeshun Shi, Cees de Laat, Paola Grosso, Zhiming Zhao
In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models.
Smart contracts are programs that are executed on a blockhain. They have been used for applications in voting, decentralized finance, and supply chain management. However, vulnerabilities in smart contracts have been abused by hackers, leading to financial losses. Understanding state machine protocols in smart contracts has been identified as important to catching common bugs, improving documentation, and optimizing smart contracts. We analyze Solidity smart contracts deployed on the Ethereum blockchain and study the prevalence of protocols and protocol-based bugs, as well as opportunities for gas optimizations.
Abstract This study furthers recent research on Initial Coin Offerings (ICO) in understanding the set of characteristics that drive ICO performance and reduce information asymmetry. Using data on 166 ICOs and more than 300,000 contribution addresses that sent funds to ICOs in Bitcoins or in Ether between 2013 and 2017, we examined the effect of ICO characteristics on ICO performance. We found that three boundary conditions predict ICO fundraising amount, number of investors, hard cap achievement and token ranking. These are registering ICO and publishing project’s code on GitHub, obtaining VC or Business angel financing before the campaign or during presale, and finally, publishing the whitepaper before the campaign’s start. Other factors such as serial investors, presale of tokens, bonus sales and funders' ownership share explain ICO performance. We offer implications for ICO investors and policymakers.
Ethereum Improvement Proposal (EIP) 1559 was recently implemented to transform Ethereum's transaction fee market. EIP-1559 utilizes an algorithmic update rule with a constant learning rate to estimate a base fee. The base fee reflects prevailing network conditions and hence provides a more reliable oracle for current gas prices. Using on-chain data from the period after its launch, we evaluate the impact of EIP-1559 on the user experience and market performance. Our empirical findings suggest that although EIP-1559 achieves its goals on average, short-term behavior is marked by intense, chaotic oscillations in block sizes (as predicted by our recent theoretical dynamical system analysis [1]) and slow adjustments during periods of demand bursts (e.g., NFT drops). Both phenomena lead to unwanted inter-block variability in mining rewards. To address this issue, we propose an alternative base fee adjustment rule in which the learning rate varies according to an additive increase, multiplicative decrease (AIMD) update scheme. Our simulations show that the latter robustly outperforms the EIP-1559 protocol under various demand scenarios. These results provide evidence that variable learning rate mechanisms may constitute a promising alternative to the default EIP-1559-based format and contribute to the ongoing discussion on the design of more efficient transaction fee markets.
This study proposes a simple two-period model to consider consumers’ borrowing behaviour in a decentralised consensus and information distribution platform. Based on this model, we develop a bank risk mitigation framework and find that decentralised digital identity and encryption technology are the most important factors for attaining market equilibrium between decentralised consensus and information distribution. Specifically, the greater the scope of digital identity construction and the more blockchain consensus records there are, the less likely the borrower will default. Our study provides meaningful practical implications for bankers and policy regulators to help them better understand consumers’ borrowing behaviour and decisions to default.
A key component of blockchain technology is the ledger, viz., a database\nthat, unlike standard databases, keeps in memory the complete history of past\ntransactions as in a notarial archive for the benefit of any future test. In\nsecond-generation blockchains such as Ethereum the ledger is coupled with smart\ncontracts, which enable the automation of transactions associated with\nagreements between the parties of a financial or commercial nature. The\ncoupling of smart contracts and ledgers provides the technological background\nfor very innovative application areas, such as Decentralized Autonomous\nOrganizations (DAOs), Initial Coin Offerings (ICOs) and Decentralized Finance\n(DeFi), which propelled blockchains beyond cryptocurrencies that were the only\nfocus of first generation blockchains such as the Bitcoin. However, the\ncurrently used implementation of smart contracts as arbitrary programming\nconstructs has made them susceptible to dangerous bugs that can be exploited\nmaliciously and has moved their semantics away from that of legal contracts. We\npropose here to recompose the split and recover the reliability of databases by\nformalizing a notion of contract modelled as a finite-state automaton with\nwell-defined computational characteristics derived from an encoding in terms of\nallocations of resources to actors, as an alternative to the approach based on\nprogramming. To complete the work, we use temporal logic as the basis for an\nabstract query language that is effectively suited to the historical nature of\nthe information kept in the ledger.\n
The use of Artificial Intelligence (AI), in particular sequential decision-making (SDM) algorithms, in blockchains can greatly improve their autonomy and general features. In this context, this paper proposes the protocol CONDOR (Connecting ai-based Oracles to blockchaiN via an auDitable auctiOn pRotocol) between a smart contract and some off-chain AI-based oracles to enable the smart contract to choose among AI solution proposals while inciting those oracles to provide non-forged results. The main principle is to consider the AI outcomes as auctions that can be challenged and audited through a dispute phase. An Ethereum implementation of the aforementioned protocol was built in order to assess its scalability and time performances.
Ceren Kocaoğullar, Arthur Gervais, Benjamin Livshits
While quantitative automation related to trading crypto-assets such as ERC-20 tokens has become relatively commonplace, with services such as 3Commas and Shrimpy offering user-friendly web-driven services for even the average crypto trader, we have not yet seen the emergence of on-chain trading as a phenomenon. We hypothesize that just like decentralized exchanges (DEXes) that by now are by some measures more popular than traditional exchanges, process in the space of decentralized finance (DeFi) may enable attractive online trading automation options. In this paper we present ChainBot, an approach for creating algorithmic trading bots with the help of blockchain technology. We show how to partition the computation into on- and off-chain components in a way that provides a measure of end-to-end integrity, while preserving the algorithmic "secret sauce". Our system is enabled with a careful use of algorithm partitioning, zero-knowledge proofs and smart contracts. We also show that with layer-2 (L2) technologies, trades can be kept private, which means that algorithmic parameters are difficult to recover by a chain observer. Our approach offers more transparent access to liquidity and better censorship-resistance compared to traditional off-chain trading approaches. We develop a sample ChainBot and train it on historical data, resulting in returns that are up to 2.4x the buy-and-hold strategy, which we use as our baseline. Our measurements show that across 1000 runs, the end-to-end average execution time for our system is 48.4 seconds. We demonstrate that the frequency of trading does not significantly affect the rate of return and Sharpe ratio, which indicates that we do not have to trade at every block, thereby significantly saving in terms of gas fees. In our implementation, a user who invests \$1,000 would earn \$105, and spend \$3 on gas; assuming a user pool of 1,000 subscribers.
U ovom radu prikazana je izrada web aplikacije za simulaciju razmjene kriptovalute Bitcoin. Ova aplikacija je razvijena s ciljem da omogući korisniku testiranje trgovanja kriptovaluta, a specifično se koristi kriptovaluta Bitcoin. Aplikacija se sastoji od korisničkog sučelja (engl. frontend) te poslužiteljskog dijela (engl. backend). Korisničko sučenje web aplikacije služi za prikaz i upravljanje resursima te razmjenu valuta. Pruža korisnicima mogućnost izrade novog računa, podizanje novih narudžbi te pregled povijesti narudžbi i transakcija. Poslužiteljski dio aplikacije se koristi za pohranu podataka o korisnicima i njihovim narudžbama kao i oblikovanje podataka iz baze za korisničko sučelje. Glavna funkcija poslužiteljskog dijela je spajanje korisničkih narudžbi i obrade transakcija među narudžbama.
Blockchains are traditionally blind to the real world. This implies reliance on third parties called oracles when extrinsic data are needed for smart contracts. Oracle implementation, however, is still controversial and debated due to the reintroduction of trust and a single point of failure. The blindness to the real world also makes blockchains unable to communicate with each other, preventing any form of interoperability. This limitation prevents, for example, liquidity held in Bitcoin from flowing into DeFi applications. An early approach to the interoperability issue is constituted by “wrapped tokens”, representing blockchain native tokens issued on a non-native blockchain. Similar to how oracles reintroduce trust and a single point of failure, the issuance of wrapped tokens involves third parties whose characteristics need to be considered when evaluating the advantages of “crossing-chains”. This paper provides an overview of the available wrapped tokens and the main issuing procedures. Benefits, limitations, and implications for trust are listed and discussed.
Kushal Babel, Philip Daian, Mahimna Kelkar, Ari Juels
We introduce the Clockwork Finance Framework (CFF), a general purpose, formal verification framework for mechanized reasoning about the economic security properties of composed decentralized-finance (DeFi) smart contracts. CFF features three key properties. It is contract complete, meaning that it can model any smart contract platform and all its contracts--Turing complete or otherwise. It does so with asymptotically constant model overhead. It is also attack-exhaustive by construction, meaning that it can automatically and mechanically extract all possible economic attacks on users' cryptocurrency across modeled contracts. Thanks to these properties, CFF can support multiple goals: economic security analysis of contracts by developers, analysis of DeFi trading risks by users, fees UX, and optimization of arbitrage opportunities by bots or miners. Because CFF offers composability, it can support these goals with reasoning over any desired set of potentially interacting smart contract models. We instantiate CFF as an executable model for Ethereum contracts that incorporates a state-of-the-art deductive verifier. Building on previous work, we introduce extractable value (EV), a new formal notion of economic security in composed DeFi contracts that is both a basis for CFF and of general interest. We construct modular, human-readable, composable CFF models of four popular, deployed DeFi protocols in Ethereum: Uniswap, Uniswap V2, Sushiswap, and MakerDAO, representing a combined 24 billion USD in value as of March 2022. We use these models along with some other common models such as flash loans, airdrops and voting to show experimentally that CFF is practical and can drive useful, data-based EV-based insights from real world transaction activity. Without any explicitly programmed attack strategies, CFF uncovers on average an expected $56 million of EV per month in the recent past.
With the advent of smart contracts, the benefits of decentralization offered by distributed ledger technologies could be implemented in sectors other than cryptocurrencies, such as Healthcare, Supply Chain, and Finance. Smart contracts, however, need oracles to fetch data from the real world, which, on the other hand, do not offer the same characteristics of decentralization as blockchain. Despite their importance, research on oracles is still in its infancy, and academic contribution on the subject is scarce and sporadic. With a bibliometric analysis, this study aims to shed light on the institutions and authors that are actively contributing to the oracle literature with the aim of promoting progress and cooperation. The study shows that although there is still a lack of collaboration worldwide, there are authors and institutions working in similar directions. On the other hand, it can be observed that most of the areas of research are poorly addressed while others are even uncovered.
Blockchains are gaining momentum due to the interest of industries and people in \emph{decentralized applications} (Dapps), particularly in those for trading assets through digital certificates secured on blockchain, called tokens. As a consequence, providing a clear unambiguous description of any activities carried out on blockchains has become crucial, and we feel the urgency to achieve that description at least for trading. This paper reports on how to leverage the \emph{Ontology for Agents, Systems, and Integration of Services} ("\ONT{}") as a general means for the semantic representation of smart contracts stored on blockchain as software agents. Special attention is paid to non-fungible tokens (NFTs), whose management through the ERC721 standard is presented as a case study.
A Futuristic Operating transactions Reaching beyond Territorial borders In blockchain Smart contract model (Fortis-ámyna) for cross border transactions in a quantum setting is proposed. A simple hybrid classical-quantum model has been described whose main ingredients are a classical blockchain capable of handling stateful smart contracts with quantum defence. This hybrid payment model uses quantum states as bank transactions and a classical blockchain to settle disputes and keep track of the valid reference numbers. The proposed model fortis ámyna has several desirable properties like de-centralized, requiring no trust in any single entity; Quick payments as quantum communication, regardless of the total number of users to speed up the transactions. In addition, fortis ámyna handles the situation in lighting speed in quantum bank-transaction if failed or has error due to connectivity, helping the initiator to track back the transaction from origin. This fortis ámyna model has tremendous advantages regarding speed, security, and authentication, guarding against quantum breaches. Ensuring more authenticity to customers and creating by linking a Distinct (De-Centralized) Identifier with blockchain’s current transaction state eventually leads to the updated digital ledger.
The recently proposed Uniswap v3 replaces the fungible liquidity provider token (LP token) into non-fungible ones, making the design for liquidity mining more difficult. In this paper, we propose a flexible liquidity mining scheme that realizes the overall liquidity distribution through the fine control of local rewards. From the liquidity provider's point of view, the liquidity provision strategy forms a multiplayer zero-sum game. We analyze the Nash Equilibrium and the corresponding strategy, approximately, deploying the liquidity proportional to the reward distribution, in some special cases and use it to guide the general situations. Based on the strategic response above, such a scheme allows the mining rewards provider to optimize the distribution of liquidity for the purpose such as low slippage and price stabilization.
The rise of Ethereum and other blockchains that support smart contracts has led to the creation of decentralized exchanges (DEXs), such as Uniswap, Balancer, Curve, mStable, and SushiSwap, which enable agents to trade cryptocurrencies without trusting a centralized authority. While traditional exchanges use order books to match and execute trades, DEXs are typically organized as constant function market makers (CFMMs). CFMMs accept and reject proposed trades based on the evaluation of a function that depends on the proposed trade and the current reserves of the DEX. For trades that involve only two assets, CFMMs are easy to understand, via two functions that give the quantity of one asset that must be tendered to receive a given quantity of the other, and vice versa. When more than two assets are being exchanged, it is harder to understand the landscape of possible trades. We observe that various problems of choosing a multi-asset trade can be formulated as convex optimization problems, and can therefore be reliably and efficiently solved.
The rise of Ethereum and other blockchains that support smart contracts has\nled to the creation of decentralized exchanges (DEXs), such as Uniswap,\nBalancer, Curve, mStable, and SushiSwap, which enable agents to trade\ncryptocurrencies without trusting a centralized authority. While traditional\nexchanges use order books to match and execute trades, DEXs are typically\norganized as constant function market makers (CFMMs). CFMMs accept and reject\nproposed trades based on the evaluation of a function that depends on the\nproposed trade and the current reserves of the DEX. For trades that involve\nonly two assets, CFMMs are easy to understand, via two functions that give the\nquantity of one asset that must be tendered to receive a given quantity of the\nother, and vice versa. When more than two assets are being exchanged, it is\nharder to understand the landscape of possible trades. We observe that various\nproblems of choosing a multi-asset trade can be formulated as convex\noptimization problems, and can therefore be reliably and efficiently solved.\n
In recent years, Blockchain technology has evolved from its original application in cryptocurrency and can now be used for applications such as Smart Contracts. Smart Contracts automatically Execute transactions without the need for a central authority however there are very few use cases of the technology, particularly amongst UK AEC Design SMEs. This paper uses a hybrid method approach which combines questionnaires with semi-structured interviews to create a framework which showcases how a Smart Contract invoicing process could work for Design SMEs. This could create an automated invoicing process which is more efficient and reduces the risk of late payment.
Monik Raj Behera, Sudhir K. Upadhyay, Suresh Shetty
Over the recent years, Federated machine learning continues to gain interest\nand momentum where there is a need to draw insights from data while preserving\nthe data provider's privacy. However, one among other existing challenges in\nthe adoption of federated learning has been the lack of fair, transparent and\nuniversally agreed incentivization schemes for rewarding the federated learning\ncontributors. Smart contracts on a blockchain network provide transparent,\nimmutable and independently verifiable proofs by all participants of the\nnetwork. We leverage this open and transparent nature of smart contracts on a\nblockchain to define incentivization rules for the contributors, which is based\non a novel scalar quantity - federated contribution. Such a smart contract\nbased reward-driven model has the potential to revolutionize the federated\nlearning adoption in enterprises. Our contribution is two-fold: first is to\nshow how smart contract based blockchain can be a very natural communication\nchannel for federated learning. Second, leveraging this infrastructure, we can\nshow how an intuitive measure of each agents' contribution can be built and\nintegrated with the life cycle of the training and reward process.\n
Asif Bhat, Rizal Mohd Nor, Md Amiruzzaman, Md. Rajibul Islam
Blokchain is used in a variety of applications where trustworthy computing is\nre-quired. Trade finance is one of these areas that would benefit immensely\nfrom a decentralized way of doing transactions. This paper presents the\npreliminary as-sessment of Accepire-BT, a software platform developed for the\npractice of col-laborative Trade Finance. The proposed solution is enforced by\nsmart contracts using Solidity, the underlying programming language for the\nEthereum block-chain. We evaluated the performance in the Rinkeby test network\nby using Remix and MetaMask. The results of the preliminary trial show that\nsmart contracts take less than one minute per cycle. Also, we present a\ndiscussion about costs for us-ing the public Ethereum Rinkeby network.\n
Runtime monitoring comes at a runtime cost. Overheads induced by monitoring and verification code may be necessary, and yet prohibitive in certain circumstances. When verification is local to a single unit of execution in a system, one can choose whether or not to monitor based on the risk of that individual unit. In this paper, we propose a monitoring and verification approach for a class of long-lived transaction-based systems whose execution can be partitioned into separate subtraces, one for each such transaction, and which are independent of each other from a correctness perspective. We focus on the use of this approach for the monitoring of smart contracts on distributed ledger technologies to show how we can reduce overheads in this manner.