Bitcoin users can offer fees to the miners who record transactions on the blockchain. We document the blockchain rarely runs at capacity, even though there appears to be excess demand and higher fee orders are not always prioritized. We show this is inconsistent with competitive mining, but is consistent with miners exercising market power. If users believe that only high fee transactions will be executed expeditiously then we show how strategic capacity management can be used to increase fee revenue. Using a novel data set, we present evidence consistent with strategic capacity management. We show that mining pools facilitate collusion, and estimate that they have extracted least 300 million USD a year in excess fees by making processing capacity artificially scarce.
Jiaming Ye, Mingliang Ma, Yun Lin, Lei Ma · 6 authors
Recent years have seen smart contracts are getting increasingly popular in building trustworthy decentralized applications. Previous research has proposed static and dynamic techniques to detect vulnerabilities in smart contracts. These tools check vulnerable contracts against several predefined rules. However, the emerging new vulnerable types and programming skills to prevent possible vulnerabilities emerging lead to a large number of false positive and false negative reports of tools. To address this, we propose Vulpedia, which mines expressive vulnerability signatures from contracts. Vulpedia is based on the relaxed assumption that the owner of contract is not malicious. Specifically, we extract structural program features from vulnerable and benign contracts as vulnerability signatures, and construct a systematic detection method based on detection rules composed of vulnerability signatures. Compared with the rules defined by state-of-the-arts, our approach can extract more expressive rules to achieve better completeness (i.e., detection recall) and soundness (i.e., precision). We further evaluate Vulpedia with four baselines (i.e., Slither, Securify, SmartCheck and Oyente) on the testing dataset consisting of 17,770 contracts. The experiment results show that Vulpedia achieves best performance of precision on 4 types of vulnerabilities and leading recall on 3 types of vulnerabilities meanwhile exhibiting the great efficiency performance.
In the late 1980s and early 1990s the electronic markets hypothesis offered a prediction about effect of information technology on industrial organisation, and many business writers forecast significant changes to the shape and nature of the firm. However, these changes did not come to pass. This paper provides an economic analysis of why, using the transaction cost economic framework of Ronald Coase and Oliver Williamson. Non-hierarchical corporate organisation struggled against contracting problems in the presence of possible opportunistic behaviour. Technologies of trust offer an institutional mechanism that acts on the margin of trust, suppressing opportunism. The paper concludes that blockchain technology provides an economic infrastructure for the coordination of economic activity and the possible realisation of the electronic markets hypothesis.
In this paper, we propose a distributed market mechanism powered by the blockchain technology addressing network ownership models in multiple telecommunications networks use cases. The proposed model is based on the smart contract technology and enables transparent and trusted bilateral trades, where trust among the network operators does not exist, and there is no impartial third-party entity who is trusted by all of the participants. We use an open source permissioned blockchain framework called Hyperledger Fabric to investigate the performance of the distributed market mechanism in cloud environments. After running experiments on Hyperledger Fabric, we discuss the practical feasibility and possible design choices of our blockchain approach based on latency, throughput and resource consumption analysis.
Shaofu Lin, Jingwen Li, Xiaofeng Jia, Jingqiu Gong
Rights confirmation is the prerequisite and a major problem in the sharing of government data resources. In the traditional sharing model, some problems restrict the sharing and opening of government data, such as unclear rights and responsibilities, unclear boundaries of ownership and use rights, artificial manipulation and so on. Based on the underlying platform of block chain, this paper uses the smart contract technology to ensure the unique data source of government data resources and the separation of the data ownership and data use rights, so as to solve the problem of confirming the rights of government data from the source of data flow.
Recent technological evolution enables Artificial Intelligence (AI) model training by users' mobile devices, which accelerates decentralized big data analysis. In particular, Federated Learning (FL) is a key enabler to realize decentralized AI model update without user's privacy disclosure. However, since the behaviour of workers, who are assigned a training task, cannot be monitored, the state-of-the-art methods require a special hardware and/or cryptography to force the workers behave honestly, which hinders the realization. Furthermore, although blockchain-enabled FL has been proposed to give workers reward, any rigorous reward policy design has not been discussed. In this paper, to tackle these issues, we present a novel method using mechanism design, which is an economic approach to realize desired objectives under the situation that participants act rationally. The key idea is to introduce repeated competition for FL so that any rational worker follows the protocol and maximize their profits. With mechanism design, we propose a generic full-fledged protocol design for FL on a public blockchain. We also theoretically clarify incentive compatibility based on contest theory which is an auction-based game theory in economics.
Nicolas Lagaillardie, Mohamed Aimen Djari, Önder Gürcan
Fairness is a crucial property for blockchain systems since it affects the participation: the ones that find the system fair tend to stay or enter, the ones that find the system unfair tend to leave. While current literature mainly focuses on fairness for Bitcoin-like blockchains, little has been done to analyze Tendermint. Tendermint is a blockchain technology that uses a committee-based consensus algorithm, which finds an agreement among a set of block creators (called validators), even if some are malicious. Validators are regularly selected to the committee based on their investments. When a validator does not have enough asset to invest, it can increase it with the help of participants that delegate their assets to the validators (called delegators). In this paper, we implement the default Tendermint model and a Tendermint model for fairness in a multi-agent blockchain simulator where participants are modeled as rational agents who enter or leave the system based on their utility values. We conducted experiments for both models where agents have different investment strategies and with various numbers of delegators. In the light of our experimental evaluation, we observed that while, for both models, the fairness decreases and the system shrinks in the absence of delegators, the fairness increases, and the system expands for the second model in the presence of delegators.
We present a model/executable specification of smart contract execution in Coq. Our formalization allows for inter-contract communication and generalizes existing work by allowing modelling of both depth-first execution blockchains (like Ethereum) and breadth-first execution blockchains (like Tezos). We represent smart contracts programs in Coq's functional language Gallina, enabling easier reasoning about functional correctness of concrete contracts than other approaches. In particular we develop a Congress contract in this style. This contract -- a simplified version of the infamous DAO -- is interesting because of its very dynamic communication pattern with other contracts. We give a high-level partial specification of the Congress's behavior, related to reentrancy, and prove that the Congress satisfies it for all possible smart contract execution orders.
Abstract Tradable permit schemes (TPS) are market‐based policy instruments, which are claimed to be more statically and dynamically efficient in achieving their policy objectives compared to the traditional regulatory instruments. However, some researchers argue that the high level of transaction costs associated with these policy instruments might undermine their efficiency. This paper addresses this issue through exploring the use of Blockchain technology in order to lower transaction costs that arise from TPS transactions. More specifically, it identifies the benefits of using Blockchain smart contracts in implementing TPS that include: increasing the amount of relevant information available to interested actors thus reducing uncertainties; reducing the amount of irrelevant information available to interested actors thus decreasing complexities; correcting information asymmetries among the actors involved thus limiting opportunistic behaviours; lowering the need for the involvement of intermediaries thus decreasing direct monetary costs; and facilitating the linkage between buyers and sellers thus improving trading quality. These potential benefits can increase the efficiency of TPS by decreasing policy‐related transaction costs.
Motivated by the success of Bitcoin, lots of cryptocurrencies have been created, the majority of which were implemented as smart contracts running on Ethereum and called tokens. To regulate the interaction between these tokens and users as well as third-party tools (e.g., wallets, exchange markets, etc.), several standards have been proposed for the implementation of token contracts. Although existing tokens involve lots of money, little is known whether or not their behaviors are consistent with the standards. Inconsistent behaviors can lead to user confusion and financial loss, because users/third-party tools interact with token contracts by invoking standard interfaces and listening to standard events. In this work, we take the first step to investigate such inconsistent token behaviors with regard to ERC-20, the most popular token standard. We propose a novel approach to automatically detect such inconsistency by contrasting the behaviors derived from three different sources, including the manipulations of core data structures recording the token holders and their shares, the actions indicated by standard interfaces, and the behaviors suggested by standard events. We implement our approach in a new tool named TokenScope and use it to inspect all transactions sent to the deployed tokens. We detected 3,259,001 transactions that trigger inconsistent behaviors, and these behaviors resulted from 7,472 tokens. By manually examining all (2,353) open-source tokens having inconsistent behaviors, we found that the precision of TokenScope is above 99.9%. Moreover, we revealed 11 major reasons behind the inconsistency, e.g., flawed tokens, standard methods missing, lack of standard events, etc. In particular, we discovered 50 unreported flawed tokens.
Blockchain is believed to bring new opportunities to dynamic spectrum management (DSM). With features of blockchain, the traditional spectrum management method, such as the spectrum auction, can be improved. It can also help to overcome the challenges about the security or the lack of incentive mechanisms for collaboration in DSM. Moreover, with blockchain, spectrum usage of the DSM system can be recorded in a decentralized manner. In this chapter, we will discuss the potentials of blockchain for spectrum management in a systematic way and using multiple case studies.
This paper studies the multi-to-multiple energy trading mode and quotation strategy based on Block-chain intelligent contract and continuous auction mechanism. When distributed power generation entities and power consumers exist in Many-to-many form, buyers and sellers can be in the trading cycle at any time. The quotation is submitted to the smart contract address, and the quotation is continuously adjusted according to the transaction result disclosed by the smart contract. Once the price is matched, the transaction can be completed, and the transaction settlement is realized through the Block-chain intelligent contract. The IEEE13 node power distribution system is taken as an example to verify the effectiveness and feasibility of the proposed method.
In the Bitcoin system, transaction fees serve not only as the fundamental economic incentive to stimulate miners, but also as an important tuner for the Bitcoin system to define the priorities in the transaction confirmation process. In this paper, we aim to study the priority rules for queueing transactions based on their associated fees, and in turn users' decision-making in formulating their fees in the transaction confirmation queueing game. Based on the queueing theory, we first analyzed the waiting time of users under non-preemptive limited multi-priority (LMP) rule, which is formulated to adjust users' waiting time over different priorities. We then established a game-theoretical model, and analyze users' equilibrium fee decisions. Towards the end, we conducted computational experiments to validate the theoretical analysis. Our research findings can not only help understand users' fee decisions under the LMP rule, but also offer useful managerial insights in optimizing the queueing rules of Bitcoin transactions.
Different from traditional programs, which run on local machines or in the clouds, smart contracts run mostly on miners' devices; moreover, users of smart contracts have to pay fees (i.e., gases in Ethereum) to miners for executing transactions on the blockchain. Lacking of enough experiences in developing smart contracts makes writing low cost and high efficiency smart contracts becoming a very challenging task. In this work, by collating existing approaches and developing new methods for reducing gas consumption, a set of systematical step-by-step guidelines for developing low cost smart contracts is proposed. To prove its usefulness, ZoKrates verifier, a very complicated and costly contract, is used to demonstrate how our scheme can effectively cut the gas consumption down.
Abstract Although double‐entry accounting has been used for more than 600 years, today’s era of disruptive technological change utilising blockchain and FinTech has led to the emergence of another promising accounting method: triple‐entry accounting. This paper explores triple‐entry accounting, from its conception to the current state of play, using three case studies. We find that: (i) in a blockchain ecosystem, for some accounts, business entities will only need to perform a single entry internally and the opposite entry will be recorded in a public shared ledger; and (ii) triple‐entry accounting is a new and a more efficient way to address fundamental trust and transparency issues that plague current accounting systems. Triple‐entry accounting with blockchain, when properly implemented, can fundamentally improve accounting.
Rainfall is a smart contract programming model that allows mutually distrusting parties to manage assets on a distributed ledger. The model consists of a tuple space of authorized facts, and a set of production rules. Rules match on authorized facts, gaining their authority, and produce new facts with a subset of the gained authority. Rainfall allows assets such as crypto currencies to be defined in user code, rather than being baked directly into the ledger framework. Our authorization model also provides a natural privacy model, where not all rules or facts need to be revealed to all parties.
Decentralized autonomy is a long-standing research topic in information sciences and social sciences. The self-organization phenomenon in natural ecosystems, the Cyber Movement Organizations (CMOs) on the Internet, and the Distributed Artificial Intelligence (DAI), and so on, can all be regarded as its early manifestations. In recent years, the rapid development of blockchain technology has spawned the emergence of the so-called Decentralized Autonomous Organization [DAO, sometimes labeled as Decentralized Autonomous Corporation (DAC)], which is a new organization form that the management and operational rules are typically encoded on blockchain in the form of smart contracts, and can autonomously operate without centralized control or third-party intervention. DAO is expected to overturn the traditional hierarchical management model and significantly reduce organizations’ costs on communication, management, and collaboration. However, DAO still faces many challenges, such as security and privacy issue, unclear legal status, and so on. In this article, we strive to present a systematic introduction of DAO, including its concept and characteristics, research framework, typical implementations, challenges, and future trends. Especially, a novel reference model for DAO which employs a five-layer architecture is proposed. This article is aimed at providing helpful guidance and reference for future research efforts.
Summary With the increasing popularity of blockchain technologies in recent years, blockchain‐based decentralized applications (DApps for short in this paper) have been rapidly developed and widely adopted in many areas, being a hot topic in both academia and industry. Despite of the importance of DApps, we still have quite little understanding of DApps along with its ecosystem. To bridge the knowledge gap, this paper presents the first comprehensive empirical study of blockchain‐based DApps to date, based on an extensive dataset of 995 Ethereum DApps and 29,846,075 transaction logs over them. We make a descriptive analysis of the popularity of DApps, summarize the patterns of how DApps use smart contracts to access the underlying blockchain, and explore the worth‐addressing issues of deploying and operating DApps. Based on the findings, we propose some implications for DApp users to select proper DApps, for DApp developers to improve the efficiency of DApps, and for blockchain vendors to enhance the support of DApps.