Blockchain Papers

Chris Berg, Sinclair Davidson, Jason Potts

No abstract is available for this record.

Ihor Fedorovych Molotok

This paper summarizes the arguments and counterarguments within the scientific discussion on the influence of fiscal decentralization measures on the management of innovative country development. The main purpose of the research is to test the hypothesis that expenditure and revenue decentralizations have a positive impact on the management of innovative country development. Testing the hypothesis considers realization of panel data regression analysis, and consists of several stages, such as: 1) elimination of control variables multicollinearity based on the correlation analysis; 2) identification of the regression model specification (fixed or random effects model) with the help of Hausman test; 3) realization of the regression analysis and characteristic of its results (confirmation or rejection of the hypothesis). It also should be noted that country sample consists of 12 unitary European countries (Czech Republic, Denmark, Estonia, France, Hungary, Italy, Latvia, Lithuania, Poland, Slovak Republic, Slovenia, and Ukraine). Time horizon – 2008-2018. Global Innovation Index is a measure of innovative country development. At the same time, the ratio of local budget revenue to consolidated budget revenue, the rate of domestic budget expenditure to consolidated budget expenditure, the proportion of local budget tax revenue to gross local budget revenue are measures of fiscal decentralization in the research. There are also selected a set of control variables that often used in economic growth models and reflect macroeconomic perspectives of country development. However, the practical realization of the stages, as mentioned above, allow identifying that fixed effect specification of the model is more appropriate in all three cases (for three different measures of fiscal decentralization). Panel data regression analysis allows confirming the hypothesis on the positive impact of revenue fiscal decentralization and the negative impact of expenditure decentralization on innovative country development. In turn, there is no statistically significant cohesion between ratio of local budget tax revenue to gross local budget revenue and Global Innovation Index. These findings in terms of fiscal decentralization reform might be considered in order to ensure a balance between power (expenditures) redistribution from central to sub-central governments and local budget financial capacity. While in terms of innovative country development, it should be considered that the lack of local budget financial resources to cover all redistributed from central government level powers makes it impossible to invest in the development of innovation. However, the increase of local government financial capacity creates opportunities not just for essential functions financing but also advanced features investment such as innovative development. Keywords fiscal decentralization, innovation development, local budget expenditures, local budget revenue, local community.

Pedro Antonino, A. W. Roscoe

The exploitation of smart-contract vulnerabilities can have catastrophic consequences such as the loss of millions of pounds worth of crypto assets. Formal verification can be a useful tool in identifying vulnerabilities and proving that they have been fixed. In this paper, we present a formalisation of Solidity and the Ethereum blockchain using the Solid language and its blockchain; a Solid program is obtained by explicating/desugaring a Solidity program. We make some abstractions that over-approximate the way in which Solidity/Ethereum behave. Based on this formalisation, we create Solidifier: a bounded model checker for Solidity. It translates Solid into Boogie, an intermediate verification language, that is later verified using Corral, a bounded model checker for Boogie. Unlike much of the work in this area, we do not try to find specific behavioural/code patterns that might lead to vulnerabilities. Instead, we provide a tool to find errors/bad states, i.e. program states that do not conform with the intent of the developer. Such a bad state, be it a vulnerability or not, might be reached through the execution of specific known code patterns or through behaviours that have not been anticipated.

Alexandros A. Papantoniou

This essay examines whether smart contract innovation is capable of displacing the orthodox adherence to traditional contracts. This examination is underpinned by an analysis of the legality of smart contracts, through which it is exemplified that smart contracts ought to be considered legally binding instruments. The essay proceeds to explore the superiority of smart contracting on a technical and theoretical basis. The advantages generated through smart contract automaticity and enforceability present a concrete basis for undermining reliance on traditional contracts. Blockchain Technology also enhances the benefits of smart contracts by acting as a smart contract enabler through guaranteed performance and enforceability. Nevertheless, such novel technologies inevitably suffer from several shortcomings. This essay considers examples which illustrate the inflexibility of smart contracting. Apart from being susceptible to hacking and code exploitation, smart contracting is unable to deal with ambiguities and potential modifications. Overall, this suggests that the advantages of smart contract practice are currently confined to some specified limited scenarios. Smart contracts perform a different function to traditional contracting by merely guaranteeing technical enforceability as opposed to legal enforceability. This essay thus concludes that, for the time being, it is best to regard smart contracting as a supplement to traditional contracts rather than an outright displacement.

Arwa Mukhtar, Awanis Romli, Noorhuzaimi Karimah

Due to the increasing complexity of supply chains over the past years, many factors significantly contribute to lowering the supply chains performance. Poor visibility is one of the major challenging factors that lowers supply chains performance. This paper proposes a Blockchain-based supply chain network model to improve the supply chain visibility. The model focuses in improving the visibility measurements properties: information sharing, traceability, and inventory visibility. The proposed model consists of information sharing, traceability, and inventory visibility platforms based on Blockchain technology smart contract. The model built with Hyperledger platform and extend the Hyperledger Composer Supply Chain Network (HCSC) model. The research is designed to three main phases. First phase: the preliminary phase which is the literature review phase to identify the existing challenges in the domain. The second phase: the design and implementation phase which is the development steps of the proposed research model. The third phase: the evaluation phase which represent the performance evaluation of the proposed model and the comparisons between the proposed model and the existing models. In the evaluation performance, the common performance metrics Lead time and average inventory levels will be compared in the proposed model, Cloud-based information system, and the traditional supply chain. These proposed platforms offer an end-to-end visibility of products, orders, and stock levels for supply chain practitioners and customers within supply chain networks. Which helps managers’ access key information that support critical business decisions and offers essential criteria for competitiveness and therefore, enhance supply chain performance.

Tingting Song, Bo Cui, Ru Li, Jing Liu · 5 authors

Named Data Networking (NDN) is a new clean-slate architecture for the future Internet. Efficient content retrieval is the original intention of NDN design. The content retrieval process driven by content consumers in NDN includes the following challenges, consumers do not know whether the content exists and whether the content producer is reliable. Invalid interest packets could cause the occupation of limited network resources and DoS attack problem. To ensure the authenticity and integrity of the data packets, consumers need to pre-configure the trust schema, which is centralized and prone to the single point of failure problem. Blockchain has widespread attention to build trust in a distributed way, and Ethereum is a programmable blockchain, a decentralized smart contract platform. To lighten the burden of consumers, we proposed a Smart Contract-based Trusted Content Retrieval Mechanism (SCTCRM) for NDN in this paper. The mechanism contains a trustworthy information base for content and producers based on smart contracts, and provides content retrieval and name resolution services for content consumers. The purpose of this mechanism is to improve the efficiency and security of content retrieval process. We described the framework and the workflow of SCTCRM, and used Colored Petri Nets to create a formal mathematical model and analyze the security of the mechanism. Finally, the cost of storage and Gas in smart contracts are evaluated through the prototype deployment. From the results, we can see that the proposed mechanism is security and practicality.

Jun Li, Jieren Cheng, Naixue Xiong, Lougao Zhan · 5 authors

Security and privacy issues have become a rapidly growing problem with the fast development of big data in public health. However, big data faces many ongoing serious challenges in the process of collection, storage, and use. Among them, data security and privacy problems have attracted extensive interest. In an effort to overcome this challenge, this article aims to present a distributed privacy preservation approach based on smart contracts and Intel Software Guard Extensions (SGX). First of all, we define SGX as a trusted edge computing node, design data access module, data protection module, and data integrity check module, to achieve hardware-enhanced data privacy protection. Then, we design a smart contract framework to realize distributed data access control management in a big data environment. The crucial role of the smart contract was revealed by designing multiple access control contracts, register contracts, and history contracts. Access control contracts provide access control methods for different users and enable static access verification and dynamic access verification by checking the user’s properties and history behavior. Register contract contains user property information, edge computing node information, the access control and history smart contract information, and provides functions such as registration, update, and deletion. History contract records the historical behavior information of malicious users, receives the report information of malicious requestors from the access control contract, implements a misbehavior check method to determines whether the requestor has misbehavior, and returns the corresponding result. Finally, we design decentralized system architecture, prove the security properties, and analysis to verify the feasibility of the system. Results demonstrate that our method can effectively improve the timeliness of data, reduce network latency, and ensure the security, reliability, and traceability of data.

Nafis Irtija, Fisayo Sangoleye, Eirini Eleni Tsiropoulou

The sheer growth of electricity demand and the rising number of electricity-hungry devices have highlighted and elevated the need of addressing the demand response management problem in residential smart grid systems. In this article, a novel contract-theoretic demand response management (DRM) framework in residential smart grid systems is introduced based on the principles of labor economics. The residential households produce and consume electricity, acting as dynamic prosumers. Initially, the prosumers' personal electricity generation and consumption characteristics are captured by introducing the concept of prosumers' types. Then, the prosumers' and the electricity market's profit is depicted in representative utility functions. Based on the labor economics principles, Contract Theory is adopted to design the interactions among the electricity market, which offers personalized rewards to the prosumers in order to buy electricity at an announced price, and the prosumers, who offer their “effort” by paying for the purchased electricity. The contract-theoretic DRM problem is formulated as a maximization problem of the electricity market's utility, while jointly guaranteeing the optimal satisfaction of the prosumers, under the scenarios of complete and incomplete information from the electricity market's perspective regarding knowing or not the prosumers' types, respectively. The corresponding optimization problems are solved following a convex optimization approach and the optimal contracts, i.e., rewards and efforts, are determined. Detailed numerical results obtained via modeling and simulation, highlight the key operation features and superiority of the proposed framework.

Chamil W. Senarathne, Wei Jianguo

This paper sets out to explore whether the investor herding in the cryptocurrency market induces correlations in cryptocurrency returns using the methodology of Chang et al. (2000) and Galariotis et al. (2015) from a daily data sampling period of 3/30/2015 to 5/24/2019. The initial regression results show that the cross-sectional absolute deviation of return can only be explained by GSCI oil and gold index return, but no relationship exists between cross-sectional absolute deviation of return and other regression variables, such as return on CCi30, US equity risk premium and US/Euro exchange rate return. The herding regression results under normal market condition show that a strong tendency exists to herd on non-fundamental information that explains cross-sectional absolute deviation of returns. As such, cryptocurrency returns cannot be predicted on the basis of fundamental economic information (e.g., major macroeconomic announcements). Herding on non-fundamental information is found to be more pronounced during an upward-trending period of the market and other than upward-trending period. No signs of herding on fundamental information could be observed under other market conditions. Although the theory suggests that herding on non-fundamental information results in more efficient outcomes, the above findings do not encourage the diversification of traditional assets with cryptocurrency on the basis of low correlation. Since cryptocurrency lacks intrinsic value, the exchange is shown to provide a pseudo-efficient trading platform for speculative investors. Implications for future research are discussed.

Ioannis Chalkiadakis, Anna Zaremba, Gareth W. Peters, Michael J. Chantler

This paper establishes a new framework for assessing multimodal statistical causality between cryptocurrency market (cryptomarket) sentiment and cryptocurrency price processes. In order to achieve this, we present an efficient algorithm for multimodal statistical causality analysis based on Multiple-Output Gaussian Processes. Signals from different information sources (modalities) are jointly modelled as a Multiple-Output Gaussian Process, and then using a novel approach to statistical causality based on Gaussian Processes (GPs), we study linear and non-linear causal effects between the different modalities. We demonstrate the effectiveness of our approach in a machine learning application by studying the relationship between cryptocurrency spot price dynamics and sentiment time-series data specific to the crypto sector, which we conjecture influences retail investor behaviour. The investor sentiment is extracted from cryptomarket news data via methods developed in the area of statistical machine learning known as Natural Language Processing (NLP). To capture sentiment, we present a novel framework for text to time-series embedding, which we then use to construct a sentiment index from publicly available news articles. We conduct a statistical analysis of our sentiment statistical index model and compare it to alternative state-of-the-art sentiment models popular in the NLP literature. In regard to the multimodal causality, the investor sentiment is our primary modality of exploration, in addition to price and a blockchain technology-related indicator (hash rate). Analysis shows that our approach is effective in modelling causal structures of variable degree of complexity between heterogeneous data sources and illustrates the impact that certain modelling choices for the different modalities can have on detecting causality. A solid understanding of these factors is necessary to gauge cryptocurrency adoption by retail investors and provide sentiment- and technology-based insights about the cryptocurrency market dynamics.

Nir Kshetri

Several blockchain-based financial technologies and cryptocurrencies have been launched for low-income people. Blockchain?s technical potential can be used to serve the needs of unbanked and underbanked populations, but there is no evidence that these needs are being met.

Jinan Liu, Sajjadur Rahman, Apostolos Serletis

Abstract In this paper, we use a bivariate structural VAR to investigate risk spillovers from the cryptocurrency market to standard financial markets. We investigate the effects of cryptocurrency shocks on key financial markets, including the stock, bond, gold and foreign exchange markets. The results show that cryptocurrency shocks do not have statistically significant effects on standard financial markets except for the bond market. This is consistent with most of the existing literature that argues that cryptocurrencies are mostly a new and different asset class, not related to standard factors.

Christian Sturm, Stefan Jablonski

No abstract is available for this record.

Mohd Sabri Ismail, Saiful Izzuan Hussain, Mohd Salmi Md Noorani

This study explores persistent homology to detect early warning signals of the 2017 and 2019 major financial crashes in Bitcoin. Sliding window is used to obtain point cloud datasets from a multidimensional time series (Bitcoin, Ethereum, Litecoin and Ripple). We apply persistent homology to quantify transient loops that appear in multiscale topological spaces, which associated on each point cloud dataset and encode the quantified information in a persistence landscape. Temporal changes in persistence landscapes are measured via their L1-norms. Consequently, a new representative is attained, called L1-norms time series. The L1-norms is associated with indicators: autocorrelation function at lag 1, variance and mean power spectrum at low frequencies to detect the signals. By using Kendall's tau correlation and significance test, significant rising trend events that occur before major financial crashes in Bitcoin are defined as the signals. A threshold is determined to scan entire data and record all the significant rising trend events. Lastly, we compare L1-norms with residuals time series, which is another representative obtained from de-trending approach. Our result portrays that autocorrelation function at lag 1 and variance of the L1-norms successfully detect early warning signals before the 2017 and 2019 major financial crashes. However, variance of the L1-norms is better since it able to signal another 2018 major financial crash. For the residuals, no early warning signals are detected. Hence, persistent homology provides a better representative than de-trending approach. Overall, persistent homology is a promising method to detect early warning signals of major financial crashes in Bitcoin.

Massimo Bartoletti, Stefano Lande, Roberto Zunino

Covenants are linguistic primitives that extend the Bitcoin script language, allowing transactions to constrain the scripts of the redeeming ones. Advocated as a way of improving the expressiveness of Bitcoin contracts while preserving the simplicity of the UTXO design, various forms of covenants have been proposed over the years. A common drawback of the existing descriptions is the lack of formalization, making it difficult to reason about properties and supported use cases. In this paper we propose a formal model of covenants, which can be implemented with minor modifications to Bitcoin. We use our model to specify some complex Bitcoin contracts, and we discuss how to exploit covenants to design high-level language primitives for Bitcoin contracts.

Lennart Ante, Ingo Fiedler

No abstract is available for this record.

Tin Tironsakkul, Manuel Maarek, Andrea Eross, Mike Just

Mixer services purportedly remove all connections between the input (deposited) Bitcoins and the output (withdrawn) mixed Bitcoins, seemingly rendering taint analysis tracking ineffectual. In this paper, we introduce and explore a novel tracking strategy, called \emph{Address Taint Analysis}, that adapts from existing transaction-based taint analysis techniques for tracking Bitcoins that have passed through a mixer service. We also investigate the potential of combining address taint analysis with address clustering and backward tainting. We further introduce a set of filtering criteria that reduce the number of false-positive results based on the characteristics of withdrawn transactions and evaluate our solution with verifiable mixing transactions of nine mixer services from previous reverse-engineering studies. Our finding shows that it is possible to track the mixed Bitcoins from the deposited Bitcoins using address taint analysis and the number of potential transaction outputs can be significantly reduced with the filtering criteria.

Dnyaneshwar Jivanrao Ghode, Rakesh Jain, Gunjan Soni, Sarjana Singh · 5 authors

Precise information flow in a supply chain (SC) improves profitability. Distorted information in SC results in coordination and transaction issues that diminish trust between SC partners. The prime objective of the present study is to enhance transparency in SC for both suppliers and consumers and boost legitimate coordination within the SC network using Blockchain Technology (BT). BT is a tool having an open-source, decentralized, and distributed database for storing transaction information. It allows two parties to perform direct transactions using their distributed ledgers without the interference of a centralized third party to achieving more transparent transactions than traditional systems. Consequently, the architecture of BT in SC has been developed based on factors identified from the literature review that leads to offering tracking and monitoring of entire SC. Subsequently, the blockchain architecture has been tested considering transactions between manufacturer, distributor, retailer, and customer to accomplish real-time transparency. Accordingly, it has been observed that transaction errors have been minimized, transparency has been improved in SC of the manufacturing industry using BT. Moreover, this paper provides a productive relationship between BT and SC management.

Xueping Liang, Sachin Shetty, Peter Foytik, Deepak K. Tosh

Distributed Ledger Technology (DLT) utilizes an architecture that can host a large number of nodes without pre-established trust to provide decentralized services. The blockchain is the most widely used architecture of distributed ledger, where transactions across the whole network are visible to all participants in a chain to prevent tampering. However, transactions may contain sensitive information such as business contract. To secure the system and protect user privacy, we propose a multi-channel architecture that leverages Intel Software Guard Extensions (SGX). We illustrate how SGX capabilities help to defend against attacks on distributed ledgers, by way of SGX enforcement on the participating machines. We adopt the design and implementation of a two layer architecture for securing the blockchain mining process and enhancing the transaction privacy. The security analysis and performance evaluation show that the design and protocols are capable of protecting privacy, defending against adversarial attacks and scalable.

Timothy Arndt, Angela Guercio

Blockchain has emerged as a transformative technology, from its beginning as the basis of cryptocurrencies to wider applications in areas such as property registration and insurance due to its characteristic as a distributed ledger which can remove the need for a trusted third party to facilitate transaction. This spread of the technology to new application areas has been driven by the development of smart contractsblockchain-based protocols which can automatically enforce a contract. One area where the types of problems being considered for blockchain exists is higher education. Students in higher education are increasingly mobile, and in an ever more agile world, the friction and delays caused by multiple levels of administration in higher education can cause many anxieties and hardships for students. Distance learning as a primary platform for higher education promises to open up higher education to a wider range of learners than ever before. In this paper, we review the use of blockchain in higher education and experimental implementations of a blockchain-based university transcript system in order to empower students and better fit today's ever more agile society and then describe some experimental results in using blockchain for higher education transcripts.

Simon Ho

La technologie des registres distribués blockchain a perturbé et révolutionné le monde en introduisant un système transactionnel décentralisé traditionnel permettant l'échange de devises et de données de manière sécurisée. Le suivi de la chaîne d'approvisionnement est un domaine qui pourrait grandement bénéficier de cette avancée. Actuellement, les chaînes d'approvisionnement centralisées souffrent d'un manque de transparence et de contrôle des stocks pour vérifier la qualité des produits traités et éviter des problèmes tels que la contrefaçon. Le processus de gestion de la chaîne d'approvisionnement traditionnel insuffisant pour localiser un produit tout au long du processus de développement et de transport et conduit à la nécessité de réorganiser la manière de gérer la traçabilité des biens de consommation. Cette thèse tente d'évaluer la faisabilité de l'utilisation d'une chaîne d'approvisionnement avec un système de registres distributés IOTA pour des applications IoT. Pour valider le concept, une chaîne logistique pharmaceutique est mise en œuvre pour obtenir des données de capteurs de température, d'humidité et GNSS à partir d'un microprocesseur à faible puissance et à faible coût pour stocker et envoyer de manière fiable et sécurisée des données et les envoyer à une nouvelle structure de chaîne de blocs. Nous en faisons la démonstration avec un CC2650 SensorTag en tant que dispositif de systèmes intégrés, le X-NUCLEO-GNSS1A1 pour le module de positionnement et un Raspberry Pi 3, proxy IOTA, pour mesurer le temps, l’énergie et l’efficacité de la création de transactions et le calcul du \guillemotleft proof of work \guillemotright. Nous analysons également les résultats de l'expérience et discutons des avantages et des inconvénients de la mise en œuvre

Douglas W. Arner, Ross P. Buckley, Dirk Andreas Zetzsche, Anton N. Didenko

No abstract is available for this record.

Haya R. Hasan, Khaled Salah, Raja Jayaraman, Junaid Arshad · 7 authors

COVID-19 has emerged as a highly contagious disease which has caused a devastating impact across the world with a very large number of infections and deaths. Timely and accurate testing is paramount to an effective response to this pandemic as it helps identify infections and therefore mitigate (isolate/cure) them. In this paper, we investigate this challenge and contribute by presenting a blockchain-based solution that incorporates self-sovereign identity, re-encryption proxies, and decentralized storage, such as the interplanetary file systems (IPFS). Our solution implements digital medical passports (DMP) and immunity certificates for COVID-19 test-takers. We present smart contracts based on the Ethereum blockchain written and tested successfully to maintain a digital medical identity for test-takers that help in a prompt trusted response directly by the relevant medical authorities. We reduce the response time of the medical facilities, alleviate the spread of false information by using immutable trusted blockchain, and curb the spread of the disease through DMP. We present a detailed description of the system design, development, and evaluation (cost and security analysis) for the proposed solution. Since our code leverages the use of the on-chain events, the cost of our design is almost negligible. We have made our smart contract codes publicly available on Github.

Peng Zhu, Jian Hu, Yue Zhang, Xiaotong Li

Medication quality and safety are crucial to the health of the public. Responding to the urgent need for medication information provenance and anti-counterfeiting, this study proposes a blockchain based method for medication information storage, inquiry, and anti-counterfeiting along a medication supply chain. Leveraging the features of decentralization, tamper-proof, traceability, and participative node maintenance of blockchain technology, the proposed method can assure the transparency and openness of medication supply chains. An access control policy model based on smart contract is designed to prevent medication information from being altered or disclosed at nodes of the blockchain. In addition, a point-accumulation upgrade/downgrade mechanism is introduced to improve the consensus mechanism. The proposed solution eliminates the needs for centralized institutions and third-party organizations, and provides a full record of the medication circulation process. Our simulation results show that efficiency and security are enhanced by the improved consensus algorithm and access control mechanism. As a result, our method can render high level of security and privacy protection that is critical to the integrity of a medication information management system.