Juan Cano-Benito, Andrea Cimmino, Raúl García‐Castro
Blockchain has become a pervasive technology in a wide number of sectors like industry, research, and academy. With the emergence of blockchain, new solutions with this technology to existing problems were devised, leading to the introduction of smart contracts. Smart contracts are similar to traditional contracts with the benefits provided by blockchain, such as immutability, privacy, and decentralisation. These contracts are usually defined based on a specific domain, and this domain knowledge can be represented through an ontology. Researches have explored the benefits of using domain ontologies with smart contracts, such as code generation, discovering other contracts in the network, or interaction with other contracts. Notwithstanding, the representation of smart contract languages themselves has not been studied. In this paper, we present an ontology for a well-known smart contract language, Solidity, defining all entities needed to cover the whole language and aligning it to other standardised ontologies such as EthOn, in a way to improve the knowledge of the ontology developed. Furthermore, the ontology has also been validated with already deployed contracts in the Ethereum blockchain. Thus, Solidity will be able to benefit from the advantages provided by ontologies, such as interoperability and the use of semantic web technologies.
There has been a great deal of discussion of the challenges on privacy, data interoperability and quality of Educational Professional Personal Record (EPPR). Therefore, there is a need to reassess the current models, in which various parties generate, exchange and observe a huge amount of personal data with regard to EPPR. Ethereum blockchain has shown that trusted, auditable transactions is detectible using a decentralized network of nodes accompanied by a general ledger. Thus, due to the fast-moving development of educational and professional data generators such as online universities and distance learning, requires learners to engage in detail into their EPPR as well as the educational and professional data generators. In this paper, we propose a novel decentralized framework to manage EPPR using Ethereum blockchain technology. The framework provides the owner of the EPPR a comprehensive immutable log and ease of access to their educational records across the educational record editors and consumers. Furthermore, it provides a recommender engine to endorse skills and competencies to the education record owners and similar candidates for educational records editors and consumers. Ethereum blockchain can provide solutions in terms of exchanging of data among parties by ensuring privacy, accountability and data interoperability. The aim of the proposed framework is to enable educational stakeholders (universities and employing agencies) to participate in the network as blockchain miners rewarded by pseudonymized data in compliance with General Data Protection Rules in United Arab Emirates.
Peer-review is a necessary and essential quality control step for scientific publications but lacks proper incentives. Indeed, the process, which is very costly in terms of time and intellectual investment, not only is not remunerated by the journals but is also not openly recognized by the academic community as a relevant scientific output for a researcher. Therefore, scientific dissemination is affected in timeliness, quality, and fairness. Here, to solve this issue, we propose a blockchain-based incentive system that rewards scientists for peer-reviewing other scientists' work and that builds up trust and reputation. We designed a privacy-oriented protocol of smart contracts called Ants-Review that allows authors to issue a bounty for open anonymous peer-reviews on Ethereum. If requirements are met, peer-reviews will be accepted and paid by the approver proportionally to their assessed quality. To promote ethical behavior and inclusiveness the system implements a gamified mechanism that allows the whole community to evaluate the peer-reviews and vote for the best ones.
With the wide application of blockchain in the financial field, the rise of various types of cybercrimes has brought great challenges to the security of blockchain. In order to better understand this emerging market and explore more efficient countermeasures for effective supervision, it is imperative to track transactions on blockchain-based systems. Due to the openness of Ethereum, we can easily access the publicly available transaction records, model them as a complex network, and further study the problem of transaction tracking via link prediction, which provides a deeper understanding of Ethereum transactions from a network perspective. Specifically, we introduce an embedding based link prediction framework that is composed of temporal-amount snapshot multigraph (TASMG) and present temporal-amount walk (TAW). By taking the realistic rules and features of transaction networks into consideration, we propose TASMG to model Ethereum transaction records as a temporal-amount network and then present TAW to effectively embed accounts via their transaction records, which integrates temporal and amount information of the proposed network. Experimental results demonstrate the superiority of the proposed framework in learning more informative representations and could be an effective method for transaction tracking.
The paper presents a new digital infrastructure layer for buildings and architectural assets. The infrastructure layer consists of a combination of topology graphs secured on a decentralised ledger. The topology graphs organise non-fungible digital tokens which each represent and correspond to building components, and in the root of the graph to the building itself.The paper presents background research in the relationship of building representation in the form of graphs with topology, of both manifold and non manifold nature. In parallel we present and analyse the relationship between digital representation and physical manifestation of a building, and back again. Within the digital representations the paper analyses the securing and saving of information on decentralised ledger technologies (such as blockchain). We then present a simple sample of generating and registering a non-manifold topology graph on the Ethereum blockchain as an EC721 token, i.e. a digital object that is unique, all through the use of dynamo and python scripting connected with a smart contract on the Ethereum blockchain. Ownership of this token can then be transferred on the blockchain smart contracts. The paper concludes with a discussion of the possibilities that this integration brings in terms of material passports and a circular economy and smart contracts as an infrastructure for whole-lifecycle BIM and digitally encapsulates of value in architectural designPlease write your abstract here by clicking this paragraph.
Dr Andres Guadamuz is Reader in Intellectual Property Law, University of Sussex. This article This article tackles various questions regarding non-fungible tokens (NFTs) and copyright, including whether an author can use an NFT to transfer copyright, several applications of tokens as digital rights management, and the issue of potential copyright infringement in NFTs. These questions are analysed from a UK perspective, specifically looking at cases from England and Wales and Scotland, while also covering a few relevant Court of Justice of the European Union decisions. This is a relatively recent technology, which will require a lengthier technical explanation to analyse the legal issues that are raised. In some instances, the public perception will be dealt with as well, as it has become evident that there is considerable misunderstanding not only about what an NFT really is but also about the ownership and copyright issues that surround the technology. The article analyses the use of NFTs for digital rights purposes, particularly the transfer of rights, and while assignment by electronic is it is not whether an NFT can transfer to copyright it is the of article that the of a not copyright, there be a to the In a by considerable to a potential copyright in is for use of but is also as an in in is and it for considerable of a for in it of the in is an that the with and that be a non-fungible of the NFTs are the in the and technology. This not it not for the that the that the NFT transfer not only the ownership of the digital but the be the to the This the of and several legal questions as to whether be copyright is in the of a of an but also there the that to and in a to the of the The the that of and that only the of the but not of the The from The is the in a of that are legal questions regarding the copyright and NFTs. an a of a by it and it an of a as as an NFT for with the the is an use it to transfer copyright ownership a it a an NFT of a it This article will questions from a UK perspective, specifically looking at cases from England and and Scotland, while also covering a few relevant of the Court of Justice of the European Union This is a relatively recent technology, which will require a lengthier technical explanation to analyse the legal issues In some instances, the public perception will be dealt with as well, as it has become evident that there is considerable misunderstanding not only about what an NFT really is but also about the ownership and copyright issues that surround the technology. 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This paper discusses the problems of short-term forecasting of cryptocurrency time series using a supervised machine learning (ML) approach. For this goal, we applied two of the most powerful ensemble methods including Random Forests (RF) and Stochastic Gradient Boosting Machine (SGBM). As the dataset was collected from daily close prices of three of the most capitalized coins: Bitcoin (BTC), Ethereum (ETH) and Ripple (XRP), and as features we used past price information and technical indicators (moving average). To check the effectiveness of these models we made an out-of-sample forecast for selected time series by using the one step ahead technique. The accuracy rate of the forecasted prices by using RF and GBM were calculated. The results verify the applicability of the ML ensembles approach for the forecasting of cryptocurrency prices. The out of sample accuracy of short-term prediction daily close prices obtained by the SGBM and RF in terms of Mean Absolut Percentage Error (MAPE) for the three most capitalized cryptocurrencies (BTC, ETH, and XRP) were within 0.92-2.61 %.
Hyoungsung Kim, Jaehyuk Jang, Sangjun Park, Heung-No Lee
The error-correction code proof-of-work (ECCPoW) algorithm is based on a low-density parity-check (LDPC) code. ECCPoW can impede the advent of mining application-specific integrated circuits (ASICs) with its time-varying puzzle generation capability. Previous research studies on the ECCPoW algorithm have presented its theory and implementation on Bitcoin. In this study, we have not only designed ECCPoW for Ethereum, called ETH-ECC, but have also implemented, simulated, and validated it. In the implementation, we have explained how the ECCPoW algorithm has been integrated into Ethereum 1.0 as a new consensus algorithm. Furthermore, we have devised and implemented a new method for controlling the difficulty level in ETH-ECC. In the simulation, we have tested the performance of ETH-ECC using a large number of node tests and demonstrated that the ECCPoW Ethereum works well with automatic difficulty-level change capability in real-world experimental settings. In addition, we discuss how stable the block generation time (BGT) of ETH-ECC is. Specifically, one key issue we intend to investigate is the finiteness of the mean of ETH-ECC BGT. Owing to a time-varying cryptographic puzzle generation system in the ECCPoW algorithm, the BGT in the algorithm may lead to a long-tailed distribution. Thus, simulation tests have been performed to determine whether the BGT distribution is heavy-tailed and has a finite mean. If the distribution is heavy-tailed, transaction confirmation cannot be guaranteed. In the validation, we have presented statistical analysis results based on the two-sample Anderson–Darling test and discussed how the BGT distribution satisfies the necessary to be considered an exponential distribution. Our implementation is available for download at https://github.com/cryptoecc/ETH-ECC.
Mar Gimenez-Aguilar, José M. de Fuentes, Lorena González‐Manzano, Carmen Cámara
Permanent availability makes blockchain technologies a suitable alternative for building a covert channel. Previous works have analysed its feasibility in a particular blockchain technology called Bitcoin. However, Ethereum cryptocurrency is gaining momentum as a means to build distributed apps. The novelty of this paper relies on the use of Ethereum to establish a covert channel considering all transaction fields and smart contracts. No previous work has explored this issue. Thus, a mechanism called$Zephyrus$, an information hiding mechanism based on steganography, is developed. Moreover, its capacity, cost and stealthiness are assessed both theoretically, and empirically through a prototype implementation that is publicly released. Disregarding the time taken to send the transaction to the blockchain, its retrieval and the mining time, experimental results show that, in the best case, 40 Kbits can be embedded in 0.57 s. for US$\$ $1.64, and retrieved in 2.8 s.
Open access
Advanced Steganography and Watermarking Techniques
The concept of identity has become one common research topic in security and privacy where the real identity of users must be preserved, usually covered by pseudonym identifiers. With the rise of Blockchain-based systems, identities are becoming even more critical than before, mainly due to the immutability property. In fact, many publicly accessible Blockchain networks like Ethereum rely on pseudonymization as a method for identifying subject actions. Pseudonyms are often employed to maintain anonymity, but true anonymity requires unlinkability. Without this property, any attacker can examine the messages sent by a specific pseudonym and learn new information about the holder of this pseudonym. This use of Blockchain collides with regulations because of the right to be forgotten, and Blockchain-based solutions are ensuring that every data stored within the chain will not be modified. In this paper we define a method and a tool for dealing with digital identities within Blockchain environments that are compliant with regulations. The proposed method provides a way to grant digital pseudo identities unlinked to the real identity. This new method uses the benefits of key derivation systems to ensure a non-binding interaction between users and the information model associated with their identity. The proposed method is demonstated in the Ethereum context and illustrated with a case study.
Blockchain technology, which provides digital security in a distributed manner, has evolved into a key technology that can build efficient and reliable decentralized applications (called DApps) beyond the function of cryptocurrency. The characteristics of blockchain such as immutability and openness, however, have made DApps more vulnerable to various security risks, and thus it has become of great significance to validate the integrity of DApps before they actually operate upon blockchain. Recently, research on vulnerability in smart contracts (a building block of DApps) has been actively conducted, and various vulnerabilities and their countermeasures were reported. However, the effectiveness of such countermeasures has not been studied well, and no appropriate methods have been proposed to evaluate them. In this paper, we propose a software tool that can easily perform comparative studies by adding existing/new countermeasures and labeled smart contract codes. The proposed tool demonstrates verification performance using various statistical indicators, which helps to identify the most effective countermeasures for each type of vulnerability. Using the proposed tool, we evaluated state-of-the-art countermeasures with 237 labeled benchmark codes. The results indicate that for certain types of vulnerabilities, some countermeasures show evenly good performance scores on various metrics. However, it is also observed that countermeasures that detect the largest number of vulnerable codes typically generate much more false positives, resulting in very low precision and accuracy. Consequently, under given constraints, different countermeasures may be recommended for detecting vulnerabilities of interest. We believe that the proposed tool could effectively be utilized for a future verification study of smart contract applications and contribute to the development of practical and secure smart contract applications.
Benedikt C. Eikmanns, Pascal Mehrwald, Isabell M. Welpe, Philipp Sandner
Similar to mobile operating systems, public blockchain infrastructures, such as Ethereum, represent a platform for the development of software applications. Since 2020, we observe the emergence of a rapidly evolving ecosystem of blockchain-based applications called Decentralized Finance (DeFi), which aspires to challenge traditional finance and associated business models. To explore the economic structures that constitute DeFi, we follow an interdisciplinary approach, supplementing information systems (IS) research with strategic management literature. We apply the theoretical lens of strategic groups to identify platform-specific dimensions and conceptualize DeFi as a hierarchical structured platform economy consisting of four strategic groups, namely 1) Token Management Applications, 2) Protocol Platforms, 3) Aggregation Platforms, and 4) Decentralized Financial Services Solutions. Further, we give a market overview of DeFi applications and discover archetypal attributes of the respective groups. Lastly, we present an integrated framework for the analysis of software-based platform ecosystems and derive areas for future research.
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.
The invention of the Internet has paved the way for a new world of opportunities in life, including finance. Even with the presence of this invention, the traditional financial system has failed to meet expectations set up by other technological advancements. In today’s world, almost everyone has access to the Internet, yet not all of them have bank accounts. According to a recent report from the World Bank Group, approximately 1.7 billion people worldwide still do not have any access to banks whatsoever. Although the Internet has helped transfer information from one part of the world to another within milliseconds, time and spending are still needed when it comes to financial assets. In the last few years, a growing trend toward decentralization in the financial system has been stimulated by blockchain and technological innovation. Satoshi and his unique invention, Bitcoin Blockchain, started to call for peer-to-peer transactions without intermediaries or centralization of any kind. Six years later, the invention of another blockchain, Ethereum, came into existence and has become the backbone of promising decentralized finance (DeFi). This paper provides an overview of blockchain technology, discussing the DeFi ecosystem and its possibilities regarding financially including the unbanked and improving the current financial system.
Smart contracts have been well‐received by researchers and practitioners for the unique features of automatic execution, transparency, and nontampering in a blockchain environment. However, little is known about the current development status of knowledge and practice regarding the application of smart contracts in various industries, especially from the procurement perspective. Thus, this paper aims to address the gap with a mixed method of bibliometric analysis and systematic literature review. Based on the evaluation of 174 filtered publications, the review has analyzed the current development status of this research area with its distributions in years and journals, cooperation networks between authors, institutions, and countries, keywords cooccurrence network, and classifications of the application of smart contracts. The results show the application of smart contracts has attracted global attention since 2016 with the Ethereum and Hyperledger fabric as the main platforms in various industries, especially in information communication technology (ICT), public management, supply chain, energy, finance, and healthcare. Various functions and benefits of smart contracts, as well as their potential advantages, have been identified and articulated from the procurement perspective. A research framework has also been developed to highlight future procurement needs in business operations across the industries via an integrated procurement approach of smart contracts.
Abdullah Al Omar, Abu Kaisar Jamil, Amith Khandakar, Abdur Razzak Uzzal · 7 authors
A smart city ensures quality maintenance in diverse sectors, namely citizen safety, security, healthcare, transportation, and energy. Besides, data privacy and security have become an uprising concern for Electronic Health Records (EHR) in smart cities. This is because the EHR platforms are constantly getting cyber threats from cybercriminals. On the other hand, health insurance companies offer certain specific policies that require the association of patients' financial data with EHRs. Thus, additional security concern arises as fraudulent entities can alter these insurance policies. An extra challenge is triggered as patients need to validate their identities separately while communicating with different smart healthcare entities. This is because these healthcare facilities and insurance companies ought to ensure authenticity before offering any service for an individual. Hence, we have implemented a blockchain framework to safeguard patients' personal information and insurance policy. In this paper, we propose a solution for the healthcare system that provides data privacy and transparency. Furthermore, in the proposed system, insurance policies are incorporated in blockchain via the Ethereum platform and data privacy is shielded with cryptographic tools.
Smart contract vulnerability detection draws extensive attention in recent years due to the substantial losses caused by hacker attacks. Existing efforts for contract security analysis heavily rely on rigid rules defined by experts, which are labor-intensive and non-scalable. More importantly, expert-defined rules tend to be error-prone and suffer the inherent risk of being cheated by crafty attackers. Recent researches focus on the symbolic execution and formal analysis of smart contracts for vulnerability detection, yet to achieve a precise and scalable solution. Although several methods have been proposed to detect vulnerabilities in smart contracts, there is still a lack of effort that considers combining expert-defined security patterns with deep neural networks. In this paper, we explore using graph neural networks and expert knowledge for smart contract vulnerability detection. Specifically, we cast the rich control- and data- flow semantics of the source code into a contract graph. To highlight the critical nodes in the graph, we further design a node elimination phase to normalize the graph. Then, we propose a novel temporal message propagation network to extract the graph feature from the normalized graph, and combine the graph feature with designed expert patterns to yield a final detection system. Extensive experiments are conducted on all the smart contracts that have source code in Ethereum and VNT Chain platforms. Empirical results show significant accuracy improvements over the state-of-the-art methods on three types of vulnerabilities, where the detection accuracy of our method reaches 89.15%, 89.02%, and 83.21% for reentrancy, timestamp dependence, and infinite loop vulnerabilities, respectively.
Ilhaam A. Omar, Raja Jayaraman, Mazin Debe, Khaled Salah · 6 authors
Effectively managing the healthcare supply chain (HCSC) process is crucial for healthcare providers not only during pandemics such as COVID-19 but also in their normal operations. Despite significant advances in new technologies and treatment options providers still suffer from poor procurement, ordering, forecasting, and distribution practices. Group Purchasing Organizations (GPOs) are an important stakeholder in HCSC and benefit providers with cost savings, volume discounts, and vendor selection. However, the current GPO contract process is time-consuming and lacks efficiency. Hence, our proposed solution integrates blockchain technology and decentralized storage to promote transparency, streamlines communication with stakeholders, and minimize the procurement timeline while avoiding pricing discrepancies and inaccuracies. Our solution connects all the stakeholders such as manufacturer, GPO, distributor, and provider using Ethereum network. In this paper, we propose a blockchain solution using smart contracts to automate the GPO contract process. We propose a generic framework for contracting process in the HCSC with detailed algorithms depicting various interactions among HCSC stakeholders. The smart contract code was developed and tested using Remix IDE and the code is publicly shared via Github. We discuss various security risks and present detailed cost analysis of various transactions incurred by the stakeholders. Our analysis demonstrates that the proposed blockchain-based solution is economically feasible as only a minimal transaction fee is expended by the stakeholders in the distributed network.
Jesús Correas, Pablo Gordillo, Guillermo Román‐Díez
Profiling tools have been widely used for studying the behavior of the programs with the objective of reducing the amount of resources consumed by them. Most profilers collect the information with dynamic techniques, i.e., execute an instrumented version of the program with some specific input arguments to profile the measures of interest. This article presents a novel static profiling technique for Ethereum smart contracts that, using static resource analysis, is able to generate upper-bound expressions that can be used to produce profiling information about the measure of interest. Unlike traditional profiling tools, we get upper-bounds on the measures of interest expressed in terms of the input arguments or the state variables of the smart contracts. The information that can be obtained by the upper-bounds allows us to detect gas-expensive fragments of a Solidity program or to spot resource-related vulnerabilities at specific program points of the program. Moreover, in this article we propose an automatic optimization of Solidity programs which reduces their gas consumption replacing the accesses to state variables by gas-efficient accesses to local variables. We have experimentally evaluated our technique and we have detected that 6.81% of the public functions analyzed can be optimized and 1.43% are vulnerable to execute arbitrary code.
Nishant Jagannath, Tudor Barbulescu, Karam M. Sallam, Ibrahim Elgendi · 8 authors
The Ethereum blockchain generates a significant amount of data due to its intrinsic transparency and decentralized nature. It is also referred to as on-chain data and is openly accessible to the world. Moreover, the on-chain data is timestamped, integrated, and validated into an open ledger. This important blockchain feature enables us to assess the network’s health and usage. It serves as a massive data warehouse for complex prediction algorithms that can effectively detect systemic trends and forecast future behavior. We adopt a quantitative approach using a subset of these metrics to determine the network’s true monetary value by developing a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) with the metrics most closely associated with the price as inputs. Since several hyperparameters regulate the learning process in an RNN, they are highly sensitive to their values. It is thus critical, to select optimal hyperparameters so that the training is quick and effective. Determining the optimal parameters of an RNN model is a tedious and complex process. Hence, previous studies have developed several self-adaptive approaches to determine the optimal values for various parameters effectively. However, none of the prior studies explore self-adaptive algorithms in deep learning models in conjunction with on-chain data to predict cryptocurrency prices. In this paper, we propose three self-adaptive techniques, each of which converges on a set of optimal parameters to predict the price of Ethereum accurately. We compare our results to a traditional LSTM model. Our approach exhibits 86.94% accuracy while maintaining a minimum error rate.