Blockchain-Research and Applications最新文献

The Ethereum blockchain’s smart contract is a programmable transaction that performs general-purpose computations and can be executed automatically on the blockchain. Leveraging this component, blockchain technology (BT) has grown beyond the scope of cryptocurrencies and can now be applicable in various industries other than finance. In this paper, we investigated the current trends in Ethereum-based decentralized applications (DApps) to be able to categorize and analyze the DApps to measure the complexity of smart contracts behind them, their level of security and their correlation to the maintainability of the DApps. We leveraged the source code analysis, security analysis, and the developmental metadata of the DApps to infer this correlation. Based on our findings, we concluded that the maintainability of Ethereum DApps is proportional to the code size, number of functions, and, most importantly, the number of outgoing invocations and statements in the smart contracts.

Smart contracts are self-executing programs running in the blockchain allowing for decentralised storage and execution without a middleman. On-chain execution is expensive, with miners charging fees for distributed execution according to a cost model defined in the protocol. In particular, transactions have a high fixed cost.

We present MultiCall, a transaction-batching interpreter for Ethereum that reduces the cost of smart contract executions by gathering multiple users’ transactions into a batch. Our current implementation of MultiCall includes the following features: the ability to emulate Ethereum calls and create transactions, both from MultiCall itself and using an identity unique to the user; the ability to cheaply pay Ether to other MultiCall users; and the ability to authorise emulated transactions on behalf of multiple users in a single transaction using hash-based authorisation rather than more expensive signatures. This improves upon a previous version of MultiCall. Our experiments show that MultiCall provides a saving between 57% and 99% of the fixed transaction cost compared with the standard approach of sending Ethereum transactions directly.

Besides, we also show how to prevent an economic attack exploiting the metatransaction feature, describe a generic protocol for hash-based authorisation of metatransactions, and analyse how to minimise its off-chain computational and storage cost.

Presently, there are over 500 cryptocurrency exchanges worldwide and more than 19,700 different cryptocurrencies. Despite the fact that cryptocurrency trading is possible via private peer-to-peer transactions, more than 90% of trading occurs on organised exchanges, which provide convenience and liquidity. However, centralised cryptocurrency exchanges are regarded as high-value targets by criminals and are often victims of cyberattacks. In this paper, we investigate the risk of cryptocurrency exchange closures and develop predictive models to forecast which markets will close down and which ones will remain active using publicly available data. Our models perform well and reach a high level of classification accuracy. Exchange trading volume, the availability of public information on exchange staff, exchange lifetime, and several cybersecurity features are identified as key attributes in predicting exchange closures. Nevertheless, our models do not account for all sources of risk, e.g., potential fraud and mismanagement of client funds committed by the exchanges themselves, and market participants are encouraged to carefully consider where and how they store their digital assets.

Blockchain technology has been rapidly growing since Bitcoin was invented in 2008. The most common type of blockchain system, public (permissionless) blockchain system, has some unique features that lead to a tension with the European Union’s General Data Protection Regulation (GDPR) and other similar data protection laws. In this paper, we report the results of a systematic literature review (SLR) on 114 research papers discussing and/or addressing such a tension. To the best of our knowledge, our SLR is the most comprehensive review of this tension, leading to a more in-depth and broader analysis of related research work on this important topic. Our results revealed three main types of issues: (i) difficulties in exercising data subjects’ rights such as the ‘right to be forgotten’ (RTBF) due to the immutable nature of public blockchains; (ii) difficulties in identifying roles and responsibilities in the public blockchain data processing ecosystem (particularly on the identification of data controllers and data processors); and (iii) ambiguities regarding the application of the relevant law(s) due to the distributed nature of blockchains. Our work also led to a better understanding of solutions for improving the GDPR compliance of public blockchain systems. It can help inform not only blockchain researchers and developers but also policymakers and law markers to consider how to reconcile the tension between public blockchain systems and data protection laws (the GDPR and beyond).

User-centric data sharing is essential to encourage citizens' active participation in the digital economy. One key to smart cities, a form of the digital economy, is the promotion of public use of citizen data. Nevertheless, it is not easy to utilize data without citizens’ consent. In this study, we took a technological approach to these issues. User-managed access (UMA) is a well-known framework for delegating resource access rights to others on the Internet. In UMA, authorization mechanisms are designed to be centralized so that resource owners can centrally manage access rights for various resources stored in different domains. However, the lack of transparency in the authorization mechanism is a barrier to its implementation in large-scale systems such as smart cities. In this study, we developed a blockchain-based cross-domain authorization architecture that enables a resource-sharing ecosystem in which organizations that wish to utilize data can freely trade with each other. The proposed architecture solves the transparency problem that conventional authorization systems have had by designing the authorization mechanism on blockchain technology. We implemented the proposed architecture as smart contracts and evaluated its processing performance. The resultant time required for delegating access rights and accessing resources was less than 500 ​ms. Furthermore, we found that the fluctuation in the processing time overhead was small. Based on these results, we concluded that performance degradation with the proposed architecture is minor.

The search for smart contract source codes has drawn research attention to fulfill developers’ and researchers’ needs. Yet, the existing studies are not mature enough to address smart contracts’ technical properties and functionalities. This paper proposes a system to improve the naive search for smart contract codes; for example, Etherscan has one keyword search feature without regard to the contract structure. We consider clustering smart contracts based on developers’ preferences, which increases the probability that the resulting source codes match developers’ needs. Our experimental results show a significant improvement in the complexity of the retrieved source codes of smart contracts compared with the baseline scenario using blockchain search engines (e.g., Etherscan). Our solution reduces the number of retrieved smart contract codes the developer has to check if the codes match her/his needs by 94%, 88%, 82%, or 98%, depending on the user’s search preferences.

Wash trade is a common form of volume manipulation used to attract investors into the market and mislead them into making wrong investment judgments. Wash trade transactions are even more prominent in ERC20 cryptocurrencies. In this paper, we proposed two kinds of algorithms to reserve direct evidence of wash trade based on the on-chain transaction data of ERC20 cryptocurrencies. After labeling the wash trade, we continued to obtain features of the wash trade and quantify the volume of the wash trade. Our experiments show that for most ERC20 cryptocurrencies, the rate of wash trade reached over 15%. Specifically, over 30% of UNI token transactions ​were labeled as wash trade. It is demonstrated that the activations of most ERC20 cryptocurrencies are unreal, and restoring real data is necessary for market regulation.

Research on blockchains addresses multiple issues, with one being the automated creation of smart contracts. Developing smart contract methods is more difficult than mainstream software development as the underlying blockchain infrastructure poses additional complexity. We report on a new approach to developing smart contracts with the objective of automating the process to increase developer efficiency and reduce the risk of errors introduced by software developers. To support industry adoption, we use Business Process Model and Notation (BPMN) modeling to describe an application while targeting applications in the trade vertical. We describe a system that transforms a BPMN model into a multi-modal model that combines Discrete Event (DE) modeling for concurrency with Hierarchical State Machines (HSMs) to represent application functionality. Then, further transformations are used to transform the DE-HSM model into methods in smart contracts. The system lets the modeler decide which of the independent patterns should be transformed into methods of a separate smart contract that is deployed on a sidechain for the purpose of (i) reducing processing costs and/or (ii) providing privacy so that other participants in the smart contract do not have visibility into the processing of the pattern. We also briefly describe a proof-of-concept tool we built to demonstrate the feasibility of our approach.

New blockchain platforms are launching at a high cadence, each fighting for attention, adoption, and infrastructure resources. Several studies have measured the peer-to-peer (P2P) network decentralisation of Bitcoin and Ethereum (i.e., two of the largest used platforms). However, with the increasing demand for blockchain infrastructure, it is important to study node decentralisation across multiple blockchain networks, especially those containing a small number of nodes. In this paper, we propose NodeMaps, a data processing framework to capture, analyse, and visualise data from several popular P2P blockchain platforms, such as Cosmos, Stellar, Bitcoin, and Lightning Network. We compare and contrast the geographic distribution, the hosting provider diversity, and the software client variance in each of these platforms. Through our comparative analysis of node data, we found that Bitcoin and its Lightning Network Layer 2 protocol are widely decentralised P2P blockchain platforms, with the largest geographical reach and a high proportion of nodes operating on The Onion Router (TOR) privacy-focused network. Cosmos and Stellar blockchains have reduced node participation, with nodes predominantly operating in large cloud providers or well-known data centres.

Privacy protection for smart contracts is currently inadequate. Existing solutions for privacy-preserving smart contracts either support only a limited class of smart contracts or rely on noncryptographic assumptions.

We propose a cryptographic obfuscation scheme for smart contracts based on existing blockchain mechanisms, standard cryptographic assumptions, and witness encryption. In the proposed scheme, an obfuscated smart contract does not reveal its algorithm and hardcoded secrets and preserves encrypted states. Any user can provide it with encrypted inputs and allow an untrusted third party to execute it. Although multiparty computation (MPC) among dynamically changing users is necessary, its privacy is protected if at least one user is honest. If the MPC does not finish within a period of time, anyone can cancel and restart it. The proposed scheme also supports decentralized obfuscation where even the participants of the obfuscation process cannot learn secrets in the obfuscated smart contract unless all of them are malicious. As its applications, we present a new trustless bitcoin bridge mechanism that exposes no secret key and privacy-preserving anti-money laundering built into smart contracts.