The idea of smart healthcare assumes the implementation of integrated platforms based on the Internet of Medical Things to improve the quality of medical processes. An indispensable condition for the development of smart healthcare is ensuring the security of medical data. The article presents a framework for the implementation of cryptographic proof of smart contracts in healthcare systems. The proposed architecture implements secure procedures for processing Electronic Health Records (EHRs) based on an access control array. The cryptographic proof of smart contracts ensures the security of medical data processing and also allows for non-repudiation, enforceability, and accountability of digital agreements made between system actors. We developed an open data exchange format for EHRs stored in the blockchain based on a nested tree structure and the DOM interface. The article presents algorithms for creating, executing and validating smart contracts for processing medical data contained in EHRs. The proposed solutions were subjected to empirical tests and cybersecurity assessment in terms of threat and vulnerability analysis using the risk analysis method. Steps recommended by ENISA and elements of the methodology developed by NIST were used to develop a strategy for minimizing the identified threats and vulnerabilities.
The rapid spread of cryptocurrencies is one of the most relevant trends today. One of the significant risks of their spread is the increase in energy consumption, which has a negative impact on the environment due to carbon emissions. This requires the development of a scientific toolkit for assessing relationships and predicting the impact of cryptocurrencies on energy consumption, which is the aim of this paper.With the correlational regression analysis, the model of the dependence of spending on IT sector, energy consumption of Bitcoin, Ethereum and global capitalization of the cryptocurrency market was conducted, based on statistical data from Statista.com, Сoinmarketcap.com and International Data Corporation. To check the possible relationship, tests for the adequacy of the results obtained (Fisher’s test, Student’s t-test) confirmed the correctness of coefficients for independent variables.The results showed a significant direct correlation (Multiple R is 95%) of spending on IT sector, energy consumption and global capitalization of the cryptocurrency market. The established relationships allowed predicting that Bitcoin energy consumption may reach 142 Terawatt hours per year in 2026. And its impact on environment by mining in 2022 was at least 27.4 Mt of CO2 emission.As a proposal, a conclusion was made on the expediency of linking mining to the use of certain sources of electricity production, such as “residual” natural gas, nuclear power, renewable energy sources. The obtained results and conclusions may be used as a basis for political decisions in the field of energy efficiency and climate change mitigation.
The goal of the article is to develop an innovative forecasting approach based on the Random Forest and fuzzy logic models for predicting crypto-asset prices (IFSs, PFSs, q-ROFSs). The baseline forecast horizon is 90 days (additional horizons are 30, 60, 120 and 150 days), which allows to estimate the significance of the chosen features and the impact of time on the forecast accuracy. The paper proposes an optimal data selection approach for the Random Forest and fuzzy logic models to improve the prediction of the daily closing price of Bitcoin, using online social network activity, trading parameters, technical indicators, and data on other cryptocurrencies. This paper utilizes a tree-based machine learning prediction and a fuzzy logic model for Bitcoin. The article attempts to prove that automated Bitcoin forecasting using machine learning algorithms is very effective for the cryptocurrency market. Nevertheless, the latter is characterized by high volatility, significant rate hikes of the most liquid cryptocurrencies (mainly Bitcoin). Therefore, investments in cryptocurrencies, especially long-term ones, involve significant risks. This defines the paper’s significance for investors and regulators. As shown by simulation studies of data selection approaches generalizing the accuracy performance of the Random Forest and fuzzy logic models to real preferences of forecasting, even under significant noise measurements, the proposed selection approach leads to fast convergence of estimates. The accuracy of the model’s results exceed 85.21 on a 90-day time horizon.
Victoria Tyshchenko, Світлана Ачкасова, Олексій Найденко, Serhii Kanyhin · 5 authors
The study focuses on improving the quality of using recurrent neural networks (RNNs) to predict cryptocurrency prices. The formula of the target variable for the model based on the arithmetic mean is developed, which allows us to better take into account the dynamics of cryptocurrency exchanges. The factors affecting this variable were grouped into features based on the volume of daily cryptocurrency trading, the volatility of the relevant prices, and the pre-calculated and selected signals of technical indicators. As part of the study, an algorithm for processing daily data was developed for the model. The results obtained made it possible to create a holistic model for forecasting stock prices. Two recurrent neural networks were trained: one with a long short-term memory (LSTM) and the other with a recurrent gate unit (GRU). To determine the efficiency of the models, the analysis was carried out using two key indicators: the Sortino coefficient, which measures the relative risk/reward for each additional unit of unwanted volatility, and the Sharpe ratio, which measures the return on assets, subtracting the free risk. As a result, it was found that both models have similar results in terms of accuracy (~69 %). Still, the GRU-based model showed significantly better values of the Sortino coefficients (3.13) and Sharpe’s coefficient (2.45), which allows us to conclude that it is effective on cryptocurrency exchanges. At the same time, the LSTM model requires more parameters for training than the GRU model with an identical structure, which leads to a longer training time. The obtained scientific and practical results are aimed at more efficient use of recurrent neural networks in price forecasting on cryptocurrency exchanges
<ns3:p> <ns3:bold>Background:</ns3:bold> Traditional publishing models, open access and major publishers, cannot adequately address the key challenges of academic publishing today: Speed of peer review, recognition of work and incentive mechanisms, transparency and thrust of the system. </ns3:p> <ns3:p> <ns3:bold>Methods:</ns3:bold> To address these challenges, the authors propose Decentralised Academic Publishing (DAP), which is based on the novel HashNET DLT platform. The DAP introduces several innovative components: tracking the activities of all participants in the peer review process using blockchain and smart contracts, the introduction of the Scholarly Wallet for holding reputation (non-fungible) and reward (fungible) tokens, the use of the Scholarly Wallet as the main interface to the DAP platform, the Virtual Editor that enables automatic discovery of the research area and invitation of reviewers, and finally the global database of evaluated reviewers, ranked by the quality of their previous work. </ns3:p> <ns3:p> <ns3:bold>Results:</ns3:bold> The DAP platform is in the development phase, with the design and functionalities of all modules defined. An exception is the central component of DAP, the Scholarly Wallet module, whose first prototype has already been created, tested and published. The implementation of DAP is planned for the next phase of the HorizonEurope TruBlo project and other research initiatives. The DAP platform will be connected to the publishing ecosystem: 1) as a backend system (distributed blockchain database) for existing publishing platforms and 2) as a standalone publishing platform with its own API interface. </ns3:p> <ns3:p> <ns3:bold>Conclusions:</ns3:bold> The authors believe that DAP has the potential to significantly improve academic peer review and knowledge dissemination. It is expected that the use of blockchain technology, the fast HashNET consensus platform and tokens for reward (fungible) and reputation/ranking (non-fungible) will lead to a more efficient and transparent way of rewarding all participants in the peer review process and ultimately advance scientific research. </ns3:p>
Rafael Ramos Tubino, Rémy Cazabet, Natkamon Tovanich, Céline Robardet
We study the real economic activity in the Bitcoin blockchain that involves transactions from/to retail users rather than between organizations such as marketplaces, exchanges, or other services. We first introduce a heuristic method to classify Bitcoin players into three main categories: Frequent Receivers (FR), Neighbors of FR, and Others. We show that most real transactions involve Frequent Receivers, representing a small fraction of the total value exchanged according to the blockchain, but a significant fraction of all payments, raising concerns about the centralization of the Bitcoin ecosystem. We also conduct a weekly pattern analysis of activity, providing insights into the geographical location of Bitcoin users and allowing us to quantify the bias of a well-known dataset for actor identification.
Δαμιανός Π. Σακάς, Nikolaos T. Giannakopoulos, Markos Margaritis, Νίκος Κανέλλος
Due to the volatility of the markets and the ongoing crises (COVID-19, the Ukrainian war, etc.), investors are keen to exploit any potential chances to make profits. For this reason, the idea of harvesting data from cryptocurrency market users takes an innovative step. Potential investors in supply chain firms in the fertilizer industry need to know whether the observation of data originating from the cryptocurrency market is capable of explaining their stock price variation. The authors identify the innovative utilization of cryptocurrency markets’ user analytical data to model and predict the stock price of supply chain firms in the fertilizer industry stock price. The main aim of this research is to evaluate the contribution of cryptocurrency market big data as a predicting factor for the stock price of fertilizer market firms. Such a finding improves the knowledge and decision-making of potential investors in the fertilizer market. Moreover, this study seeks to highlight the benefits of utilizing cryptocurrency market big data for other financial purposes, apart from stock price prediction. The analytical data was derived from cryptocurrency websites and applications and was then processed through statistical analysis (correlation and linear regressions), Fuzzy Cognitive Maps (FCM), and Hybrid Modeling (HM) modeling. The hybrid model’s simulation showed that analytical data from the cryptocurrency markets tend to explain and predict the stock price of supply chain firms in the fertilizer industry. Such data refer to Bitcoin’s website organic keywords and traffic costs, as well as paid traffic costs from cryptocurrency trade websites/apps. A rise in Bitcoin and cryptocurrency trade websites’ organic and paid traffic costs tend to increase supply chain firms in the fertilizer industry’s stock prices, while Bitcoin’s website organic keywords variation decreases accordingly.
The study provides detailed information about the cryptocurrency market as an IFRS object and indicates the methods of their accounting and their features. Data on the change in the total market capitalization of cryptocurrencies are shown, and the reasons for which they went into decline are revealed. Companies that may be interested in accounting for cryptocurrencies under IFRS are considered, as well as the official guidance of the IASB on the issue of accounting and reporting of cryptocurrencies, issued several years ago, is analyzed. Two standards IAS 38 "Intangible Assets" and IAS 2 "Inventories" are analyzed and the reasons why for which the company's cryptocurrency is mainly accounted for either as part of intangible assets or as part of inventories. The foreign experience of some companies that reflect the cryptocurrency according to IFRS is studied, as well as Azerbaijan's practice in this area is considered. Accounting standards have not yet been fully developed, as cryptocurrency has different characteristics from traditional financial assets. Therefore, businesses may experience uncertainty regarding the accounting of cryptocurrency. It is important for businesses to maintain proper accounting records regarding cryptocurrency. These records help businesses meet their tax obligations related to the purchase, sale and exchange of cryptocurrency. However, it can be difficult to find staff with adequate knowledge of accounting and recording cryptocurrency.
Purpose: In response to the problems of high production costs, weak comprehensive competitiveness, and incomplete capital chain in the development of enterprises in the international market, this article proposes to apply blockchain technology to the digital platform of the supply chain. By scientifically managing the digital platform, enterprises can reduce production costs and improve their capital chain. Design/methodology/approach: In this long-term economic life, theoretical science and technology are still developing, gradually forming a blockchain-based enterprise supply chain development model. The continuous research on the blockchain theory can provide more convenient services for the supply chain digital platform innovation management. Findings: This article studies the entire supply chain management process through blockchain algorithms and innovative management methods, which can enable enterprises to further develop on the digital platform of supply chain, promote the digital construction of supply chain, and ensure the sustainable development of enterprises. Originality/value: This can reduce the supply chain digital platform innovation management risk of enterprises by more than 60%, as well as reduce the cost of enterprises, which has a more far-reaching impact on the sustainable development of enterprises.
Poor payment practices are perceived as one of the biggest challenges facing the construction industry. Since payments are issued according to project contract terms, the project's cash flow is inherently affected by the contract and how parties fulfill their obligations. This research proposes a framework for payment automation in construction projects to achieve smart construction contracts. Payments are automatically issued upon satisfying contract conditions using blockchain. Cryptocurrency is proposed to be utilized in the framework to execute the contract terms with no need for a third party to process project payments. 5D BIM is used to model the geometry of buildings and visualize project progress together with payment status using Autodesk Revit, Navisworks, and Primavera P6. The developed framework has the potential to reduce the consequences of poor payments. An actual case study for a construction project in Cairo, Egypt is worked out to demonstrate the main features of the proposed framework. The results of the case study reveal that project cash flow is secured and payments are instantly issued. Moreover, electronic records of payments are kept on the blockchain.
In recent years, the market for non– fungible tokens (NFTs) has been developing steadily. The concept of tokenising the uniqueness of digital elements has emerged thanks to the Ethereum blockchain token standard. This type of token is associated with digital properties in the context of the value of properties as unique identifiers. This feature has expanded the penetration of NFTs in most industries. Despite this, the NFT ecosystem is still at an early stage of development, while the technologies on which NFTs are based are entering a mature stage of development. All this generates a large amount of unsystematic information, which complicates the process of analysing and evaluating NFT projects. This article identifies opportunities for businesses to use NFTs to help modernise and digitalise their operations. It also identifies the areas by which all NFT collections are grouped and provides criteria for differentiating assets by rarity. The study also identified the impact of the minimum price and the factors that influence it during listing. Based on the results of the analysis, a six– stage analysis of NFT projects was derived, which can be used to analyse and determine the rationality of further research for investment.
With the rapid growth of social economy and the improvement of people's living standards, the logistics industry not only shows a trend of rapid development, but also faces various business risks. Therefore, supply chain management becomes particularly important. Strengthening supply chain management has become a general trend. The traditional cost-oriented supply chain management model has been unable to meet the requirements of modern enterprise development. Given that the changes in customer demand, production, and sales have not been considered, enterprise resources are easily wasted. How to build a new supply chain model driven by value and customer demand has become one of the problems that large enterprises must solve. The combination of artificial intelligence (AI) and blockchain technology (BT) can realize information sharing, risk sharing, data interaction, and other functions. Through smart contracts, the division of responsibilities among all roles in the supply chain is controlled, which makes the supply chain safer and more efficient. In this paper, the authors designed a new supply chain financial system model that can effectively reduce financial risks, improved the efficiency of capital use, and enhanced the competitiveness of enterprises. The authors compared the traditional supply chain management mode with the management mode under the combination of AI and BT. The supply chain resource and economic security management based on AI and blockchain multichannel technology was more efficient, the system security index was higher, and the internal employee satisfaction of the enterprise also increased by 5.98%. The simulation application system for the internet of things and edge computing has the characteristics of high real-time and scalability. By analyzing the differences between the internet of things and edge computing technologies in terms of device perception, communication mode, data processing, and processing performance, product manufacturing efficiency can be improved to a certain extent.
Apr 14, 2023·CEUR Workshop Proceedings, Vol-3373: Proceedings of the 4th International Workshop on Intelligent Information Technologies & Systems of Information Security with CEUR-WS
Liliia Shumyliak, Ľuboš Cibák, С. Е. Остапов, Abdel-Badeeh M. Salem · 5 authors
Smart contracts built on blockchain technology are changing the way traditional industries and businesses operate. They allow the terms of an agreement to be automatically executed without the need for a middleman, leading to decreased administration costs, more efficient processes, and reduced risks. This article is focuses on the practical implementation of smart contracts. It discusses the benefits of using smart contracts for companies, including increased security and transparency, reduced transaction costs, and automation of contractual processes. The article also describes the key elements of a smart contract, provides a description of the implementation of smart contracts on the online market of digital goods, and presents the developed algorithm of the system operation.
Blockchain is a modern, influential technology that is already transforming organizations and their business models in all business processes, including accounting and auditing. The article identifies and analyzes the risks of blockchain application in accounting and audits of fuel and energy companies. Areas of application of blockchain in accounting and auditing of fuel and energy companies have been determined, which include - integration of cryptocurrency into the accounting system of an energy company, creation of smart contracts, certification of renewable energy sources, automation of accounting and document flow, operational management of energy company assets, accounting of accounts consumption of energy and fuel resources. The risks of using blockchain technology in accounting and auditing of fuel and energy companies are systematized, which are grouped according to the following directions: high requirements of blockchain for energy consumption, lack of sufficient knowledge and skills of accountants in working with blockchain, technical, accounting and auditing problems. An example of choosing an economic risk management strategy of an energy company using maximax, Bayes, Laplace, Wald, Savage, Hurwitz criteria has been developed. The results of the research can be useful for accountants, auditors and managers of fuel and energy companies during the implementation and use of blockchain technology in practical activities.
Sergey V. Ermakov, Sergey Kucenko, Rinat Gil'vanov
Purpose: The stages of becoming in a university of new trend “Digital Department” which allows also to formulate term “digitalization” anew. Methods: The birth of term “digitalization” in a university has been studied. The evolution of notions “automation”, “informatization”, “digitalization” which predetermine smooth transfer to new trend in universities — “digital department” and, hence, “digital university”, has been shown. Results: “Digital university” model has been formulated that consists of such important components as “infrastructure”, “programmatic platforms”, “informational systems”, “data corporative storage” and “digital services”. “Digital department” possibilities in a university have been demonstrated in the part of realization of “Digital technologies on railway transport” educational program and such notional trends as internet of things, big data, virtual and augmented reality systems, artificial intelligence, “digital twin”, distributed ledger systems (recent years major trends in digital economy sphere). Practical significance: “Digital department” possibilities from the point of uniform approach to widescale teaching digital competences to students of almost all IT specialties and training trends have been demonstrated. The experience of external control has been narrated — from making to teaching — by Science and Higher Education Ministry and Digital Development, Communication and Mass Communications Ministry of Russian Federation by means of Innopolis University. The article authors make an attempt to answer topical in this sphere questions: how modern digital services immediately influence training features in professional education? Which is management model of “digital university”? Which components it consists of?
Open access
Economic and Technological Systems Analysis
Scientific Research and Philosophical Inquiry
Advanced Research in Systems and Signal Processing
P. M. Yawalkar, Deepak Narayan Paithankar, Abhijeet Rajendra Pabale, Rushikesh Vilas Kolhe · 5 authors
An integrated identity is a centralized identifier that makes it possible for customers to get access to a variety of business services from a single network. The risks and assaults include identity leaks, centralized management, auditing restrictions, and lengthy breach investigation procedures. The article presents a technique for creating a blockchain-based, integrated identification system in a marketplace by automating and decentralizing the creation and auditing of strong and secure attributes. When individuals engage in market transactions, they act as nodes in a distributed blockchain network, contributing to the development of federated identities. Using a single federated identity, members of this network are able to use any of the participating companies' services. In this, IoT sensors and wearables can automatically log real-time data for you while identifying patterns and flagging problems. The total transparency of all blockchain transactions provides participants the ability to see which services they're using and their users the ability to track the usage of their identities. To test the proposed architecture, implementation done on a public blockchain and a permissioned blockchain (Ethereum and Hyperledger Fabric).
The paper discusses the current state and development prospects of Web3 and decentralized autonomous organizations in comparison with Web 2.0. The problems of interaction between participants of decentralized autonomous organizations within the virtual space and integration of a decentralized autonomous organization with the outside world through network inducement algorithms are raised. The possible implementation of such interactions is considered on the example of TheOoL DAO. The functionality of TheOoL DAO is briefly disclosed, aimed at ensuring the security of participants in a decentralized autonomous organization, the complete suppression of the "digital footprint" they leave. The classes and forms of financial relationships of participants in a decentralized autonomous organization are determined. A mathematical model of billing in the serverless secure Internet TheOoL DAO on smart contracts is presented as an integral part of the TheOoL cloud computing and data storage subsystem. This system provides guaranteed automatic payment for services for the provision of computing power for storing and processing data or performing computing tasks and, at the same time, performs the functions of fully automatic control over the execution of the terms of a smart contract by the owners of these capacities. The presented billing system blocks the transfer of personal information between the customer and the service provider, which ensures the privacy and security of the execution of smart contracts.
Barbara Balon, Krzysztof Kalinowski, Iwona Paprocka
This article presents the architecture of integration of blockchain technology (BCT) and the Internet of Things with the planning of production processes. The authors proposed a shared concept of a distributed machine database based on BCT. As part of the work, a network of connections for the exchange of production resources was created using nodes communicating in a decentralized system, which at the same time serves as an integration of the virtual and real environment. Particular attention was focused on developing an algorithm for the efficient division of production tasks between all interested network users. BCT is used to conclude smart contracts and transactions and ensure the security of exchanged production data within shared ledgers. The proposed concept is a solution enabling a modern approach to the interdisciplinary management of production resources while maintaining the highest cybersecurity standards.
Given the challenge of manufacturing data silos and information credibility issues in traditional aviation suppliers’ result-oriented management approach, this paper proposes a blockchain-based aviation supplier manufacturing process quality data-sharing platform. Firstly, the paper introduces the possibility of integrating manufacturing supply chain quality management with blockchain technology. Secondly, the quality and data sharing platform architecture of the production process of new aviation suppliers is presented based on quality state and island kinds of aviation suppliers. Then, a detailed method for the implementation of quality and data security sharing is proposed to support the sharing platform’s real-time and orderly operation. Build critical technologies such as manufacturing quality data block packaging models, data storage security sharing, and supplier assessment models on this foundation. Finally, depending on data collection of supplier product production processes to shared application practices based on a specific aircraft industrial park under the supervision of the platform architecture and technology. The application platform integrates the data supply and request components, providing practical and intelligent sharing solutions for airlines’ product quality data.
Cryptocurrencies have emerged as a popular investment option in recent years. This paper aims to identify and analyse the factors that determine the pricing of cryptocurrencies. The existing problem is the lack of a comprehensive framework for understanding cryptocurrency pricing. The study is necessary to help investors make informed decisions about investing in cryptocurrencies. To examine determinants of cryptocurrency prices, the study used five cryptocurrencies and employs the GMM techniques. The study used multiple variables (coin prices; coins issued per day; difficulty and market capitalisation) to test how they can determine cryptocurrency prices. Findings showed that coins that uses higher hash rate, which has higher difficulty, higher market capitalisation and has lower number of coins that are mined on daily basis, is likely to have its pricing improved over short to medium terms. Overall, this research work provides valuable insights into the factors that determine the pricing of cryptocurrencies.
The article discusses the encryption security of the Bitcoin Core cryptocurrency wallet. Particular attention is paid to aspects of the practical implementation of cryptographic algorithms when encrypting the wallet.dat file with a password. The practical strongness to brute-force attacks using parallel computing on the GPU is also considered. It was found that Bitcoin Core did not implement an encryption key change for private keys. This implementation makes it possible to re-attack the wallet without knowing the new password, if it has already been compromised before. The changes to encryption algorithms that complicate the password brute force attacks on the GPU are also proposed.
Purpose. The research aim is to study effects of cryptocurrencies inclusion into an investment portfolio. To achieve the aim, portfolios with different composition of traditional and crypto assets are to be formed and compared.Methodology. It is proposed to conduct the following steps of the appropriate algorithm of investigating modern opportunities with cryptocurrency market: 1) preliminary analysis of the relationships and interdependencies between traditional assets and crypto assets; 2) formation of the initial set of crypto assets that can be potentially included into portfolio; 3) efficient frontier assessment for portfolios with different initial composition of assets; 4) comparative assessment and result analysis.Findings. The algorithm was implemented for the initial set of five most common traditional assets and ten cryptocurrencies. The latter constituents list was formed according to the value of market capitalization. Than the initial set of crypto assets was reduced according to their multidimensional distances from traditional assets. The results obtained allow to conclude that there are opportunities of portfolio efficiency increase via crypto assets inclusion in its structure. The increase value varies noticeably and depends on the particular kind of crypto assets, their total share and number.Originality. This research suggests to conduct additional preliminary procedures to choose potential candidates to be included into the traditional portfolio among initial set of crypto assets. Firstly, market capitalization value and low correlations with traditional portfolio constituents are taken into account. Secondly, all assets are presented as points in two-dimensional risk-return space and crypto assets are chosen according to the multidimensional distance measure value.