The evolution of regulatory compliance in the financial sector has transformed enterprise data systems from basic record-keeping tools into critical strategic assets. Financial institutions face mounting regulatory requirements across jurisdictions, necessitating sophisticated technological solutions to ensure compliance while maintaining operational efficiency. This article explores how integrated regulatory reporting systems consolidate disparate data sources, real-time monitoring capabilities enable proactive compliance management, and data lake architectures provide comprehensive audit trails. It examines blockchain and distributed ledger technology's role in enhancing transparency and traceability across various compliance domains, including KYC/AML processes, securities settlement, trade finance, and cross-border payments. The article also addresses integration challenges through API-first architectures, data governance frameworks, regulatory change management, and cloud-based platforms. Finally, it explores emerging innovations such as AI-powered regulatory intelligence, predictive analytics, regulatory-as-a-service models, and cross-institutional compliance networks that represent the future of enterprise data systems in regulatory
This article explores the impacts of digital transformations and new technologies in industrial sector (particularly through the Fourth Industrial Revolution) on optimizing production processes. Characterized by key technologies such as the Internet of Things (IoT), big data analytics, artificial intelligence (AI), blockchains, and advanced robotics, Industry 4.0 has significantly shaped modern manufacturing management. IoT enables autonomous communications between machines and equipment, providing real-time insights into production parameters and enabling predictive maintenance, and big data plays a vital role by analyzing the large volumes of data that are generated by these devices, thus supporting informed management decisions. AI and machine learning help automate complex tasks, optimize production schedules, and improve product quality through real-time adjustments. Blockchain enables decentralized and secure data recording, which is particularly useful in supply-chain management. Advanced robotics increases production speed and accuracy, thus reducing labor costs and mitigating any risks that are associated with hazardous tasks. Integrating these technologies requires strategic planning, including identifying key challenges, conducting pilot projects, integrating with existing IT and OT systems, and managing organizational change. Measuring the effectiveness of Industry 4.0 implementation should involve well-defined key performance indicators (KPIs) and return-on-investment (ROI) analysis. The primary challenges that are associated with adopting Industry 4.0 include the alignment of technology with specific business needs, employee resistance to change, and hidden costs of implementation. In summary, industrial transformation offers opportunities for companies to optimize production processes, reduce costs, and increase competitiveness in the global marketplace. However, a careful approach is necessary to maximize efficiency, foster innovation, and secure long-term success in an increasingly digitalized world.
The article explores the integration of digital payment systems into e-commerce as a key factor in strengthening enterprise economic security. It emphasises the strategic role that digital payments play in ensuring financial stability, reducing operational risks, and enhancing customer trust, especially for small and medium-sized enterprises (SMEs). The study synthesises current academic discourse and industry reports, focusing on the advantages of real-time transaction processing, transparency, compliance with regulatory standards, and operational efficiency. It highlights the risks associated with cybersecurity threats, platform interoperability, and legal non-compliance. Empirical insights are drawn from the integration experiences of Eastern European SMEs using platforms such as PayPal, LiqPay, and Fondy. In addition, the article examines the transformative potential of blockchain-based systems, artificial intelligence, and decentralized finance technologies in reshaping payment infrastructures. It concludes that the integration of secure and innovative digital payment systems is not merely a technological upgrade, but a strategic necessity that directly supports economic resilience and long-term competitiveness in the digital economy.
Cryptocurrency is a novel exploration of a form of currency that proposes a decentralized electronic payment scheme based on blockchain technology and cryptographic theory. While cryptocurrency has the security characteristics of being distributed and tamper-proof, increasing market demand has led to a rise in malicious transactions and attacks, thereby exposing cryptocurrency to vulnerabilities, privacy issues, and security threats. Particularly concerning are the emerging types of attacks and threats, which have made securing cryptocurrency increasingly urgent. Therefore, this paper classifies existing cryptocurrency security threats and attacks into five fundamental categories based on the blockchain infrastructure and analyzes in detail the vulnerability principles exploited by each type of threat and attack. Additionally, the paper examines the attackers' logic and methods and successfully reproduces the vulnerabilities. Furthermore, the author summarizes the existing detection and defense solutions and evaluates them, all of which provide important references for ensuring the security of cryptocurrency. Finally, the paper discusses the future development trends of cryptocurrency, as well as the public challenges it may face.
The article is dedicated to analyzing the potential for the implementation of blockchain solutions in the activities of large agro-industrial holdings. Based on a review of current research and the generalization of pilot project experiences, key areas for applying distributed ledger technology in the agro-industrial complex have been identified: supply chain management, product quality monitoring, logistics optimization, and automation of financial transactions. An assessment of the economic impact of integrating blockchain into the business processes of agro-holdings has been conducted. The results obtained indicate significant potential for increasing companies’ efficiency and sustainability through enhanced transparency, security, and speed of operations. Barriers hindering the widespread adoption of blockchain in the agro-industrial complex have been highlighted, and measures to overcome them have been proposed. The conclusions drawn are valuable for strategic planning of digital transformation in the agricultural sector. (127 words).
Open access
Blockchain Technology Applications and Security
Digitalization and Economic Development in Agriculture
It is not uncommon for customers who intend to buy a used product in the secondary market to end up with a counterfeit because they have imperfect information about product authenticity . Blockchain is being piloted as a cutting-edge solution to this challenge. We use a two-period game to study the impact of utilizing blockchain to combat counterfeit products in the secondary market. We show that, even when the cost of implementing blockchain is negligible, the manufacturer can be better off incurring reputation damage than adopting blockchain. Further, the used goods reseller can be worse off from blockchain, even though that seller is not responsible for the implementation cost and benefits from blockchain’s signaling capability. We also demonstrate that the counterfeiter can benefit as a result of blockchain. When the quality of a fake product is sufficiently low, blockchain lowers consumer surplus . The winning situation of blockchain between the manufacturer, reseller, and customers is achieved only when the fake product is of intermediate quality. Blockchain can be powerful in situations when used products have a low perceived quality; otherwise, blockchain may not be ideal.
Methods. The application of the abstraction method allowed for the isolation of volatility characteristics, simplifying the analysis of complex financial data of the cryptocurrency market. Analysis with synthesis facilitated the identification of patterns and the integration of traditional and modern forecasting approaches, providing a comprehensive assessment of methods. Logical and historical approaches enabled evolutionary analysis, while classification methods based on general and specific analysis principles, combined with comparative and abstract-logical analysis, allowed for an objective evaluation of the developed models’ effectiveness and justified the feasibility of developing innovative solutions for optimizing trading strategies and minimizing risks. Results. The study conducted a comparative analysis of cryptocurrency market volatility prediction methods using traditional statistical approaches and modern machine learning algorithms. The results confirm the advantages of integrating classical methods with machine learning algorithms, which allow for more accurate risk assessment and optimization of trading strategies in the highly volatile cryptocurrency markets. The determined volatility can be used in conjunction with Reinforcement Learning (RL) to optimize trading strategies, allowing an agent to learn to make decisions in an environment to maximize cumulative reward. The use of RL in cryptocurrency trading is a promising direction but requires a cautious approach and thorough testing of strategies before their application in real trading.Novelty. The scientific novelty lies in a comprehensive approach to forecasting cryptocurrency market volatility, combining classical statistical methods with modern machine learning algorithms. The advantages of ensemble machine learning methods for analyzing cryptocurrency volatility have been established. The integration of Reinforcement Learning (RL) for optimizing trading strategies based on predicted volatility is proposed, representing a new approach to cryptocurrency trading automation. Practical value. The research results have practical significance for cryptocurrency market participants, including investors, traders, and financial analysts. The integration of machine learning methods with traditional statistical approaches opens new opportunities for developing effective trading strategies, contributing to increased profitability and stability in the cryptocurrency market. The research is also useful for developers of trading platforms and analytical tools, as it provides empirical data for improving prediction algorithms and market data analysis.
Andreia de Castro Costa Xavier, Cláudio Gottschalg Duque, Tomás Roberto Cotta Orlandi
This study proposes an archival management method for Electronic Health Records (EHRs) based on architectural techniques and Blockchain and Smart Contracts technologies to ensure governance, security, and privacy in Health 4.0 contexts. Given the increasing relevance of EHRs as sources of information, evidence, and research in digital healthcare ecosystems, the research highlights challenges related to data governance, interoperability, and cybersecurity. Through a qualitative, exploratory approach, the authors present a method structured in seven macro-processes, covering the EHR lifecycle from capture to permanent archival or disposal. The implementation of private Blockchain networks and Smart Contracts automates processes, guarantees data integrity, and strengthens patients' control over their personal data, aligned with legal frameworks for data protection. The findings reinforce the need for innovative archival practices and technological strategies to enhance efficiency, security, and transparency in healthcare information management.
This research aims at examining how blockchain and smart contract technologies can enhance the circular economy in construction. In this quantitative research, data was collected from 134 construction industry professionals from different countries with majority from the UK and Australia by an online questionnaire. The research targeted respondents who possessed certain levels of experience in the field of engineering, construction, project management, and consultation and, therefore, used purposive sampling. An analysis of the survey data indicated that there was a level of support for the application of blockchain (BC) and smart contract (SC) technologies in enhancing circular economy practises. Industry professionals provided higher consensus regarding the benefits of these technologies for promoting circular economy in construction, with mean scores in all the statements above 4.6 on a 5-point scale. The pre to posttest findings were statistically significant t (58.00) p < .000 indicating that the participants’ views shifted from being neutral about the technologies’ advantages. From these findings, the research suggests awareness creation and training, implementation partnership models, policy and incentives support, and more research on the application of BC and SC technologies in the construction sector circular economy.
The significant overflow of the cup, symbolizing the total capacity of the world’s real assets, with a superior flow of world financial assets leads to the ongoing spread of excess financial assets, inflating another financial bubble since 2008, in various directions. The ongoing unrestrained emission of money by the «golden antelope» represented by the Federal Reserve System leads to numerous market transformations that distort the picture of the equilibrium market, turning the world economy into a kingdom of crooked mirrors. Many countries could not decide for a long time on recognizing the legitimacy of cryptocurrency transactions at the state level. However, under the pressure of increasing volumes of financial flows generated at the instigation of the states themselves, more and more countries began to officially recognize cryptocurrency transactions. In 2024, Russia joined this list, which makes it relevant to analyze the likely impact of the global cryptocurrency market on the development of the national economy. The purpose of the presented studies is to analyze the expected impact of the development processes of global cryptocurrency markets on the domestic market. The scientific novelty of the obtained results lies in the analysis of the current state of affairs on cryptocurrency exchanges and their comparison with traditional exchanges, the speculative nature of crypto transactions, trading volumes that determine the size of cryptocurrency exchanges, indicators of manipulation in the cryptocurrency market, key results of trading on cryptocurrency exchanges, etc. The practical significance of the obtained results lies in the development of proposals to reduce the risks associated with cryptocurrency transactions that affect both the financial system of Russia and the economy of the country as a whole.
As a result of the conducted research, it has been revealed that the scientific and practical literature lacks sufficient studying of the functioning and systematisation of existing data on new financial technologies, on the basis of which modern financial services and products are developed. There-fore, the features of distributed ledger technology (hereinafter referred to as DLT) are chosen as the subject of research in this work . The purpose of the study is to analyse the application of the DLT in modern conditions based on exploring theoretical and practical aspects of the problem under study. In accordance with the set purpose, the objectives are to identify the features of the DLT, to develop a classification of this technology according to appropriate criteria as well as to identify the directions of regulating the use of the DLT in modern conditions. The sources of information are informational and analytical materials and empirical data from open sources of both public authorities and commercial organisations. In the course of the study, the features of the DLT are considered, the criteria for its classification are presented as well. Based on the results of the conducted study, it has been concluded that the features of the DLT described by us are fragmentary reflected in regulatory legal acts, which once again emphasises the need to develop common guidelines for public policy in relation to the legal and technical regulation of the DLT in Russia.
In today's financial landscape, individuals face challenges when it comes to determining the most effective investment strategies. Cryptocurrencies have emerged as a recent and enticing option for investment. This paper focuses on forecasting the price of Ethereum using two distinct methods: artificial intelligence (AI)-based methods like Genetic Algorithms (GA), and econometric models such as regression analysis and time series models. The study incorporates economic indicators such as Crude Oil Prices and the Federal Funds Effective Rate, as well as global indices like the Dow Jones Industrial Average and Standard and Poor's 500, as input variables for prediction. To achieve accurate predictions for Ethereum's price one day ahead, we develop a hybrid algorithm combining Genetic Algorithms (GA) and Artificial Neural Networks (ANN). Furthermore, regression analysis serves as an additional prediction tool. Additionally, we employ the Autoregressive Moving Average (ARMA) model to assess the relationships between variables (dependent and independent variables). To evaluate the performance of our chosen methods, we utilize daily historical data encompassing economic and global indices from the beginning of 2019 until the end of 2021. The results demonstrate the superiority of AI-based approaches over econometric methods in terms of predictability, as evidenced by lower loss functions and increased accuracy. Moreover, our findings suggest that the AI approach enhances computational speed while maintaining accuracy and minimizing errors.
V. S. Balatska, R. L. Tkachuk, A. I. Ivanusa, V. I. Yashchuk · 5 authors
Problem. The growing intensity of cyberattacks on state registers and the increasing complexity of insider threats expose the weaknesses of traditional comprehensive information security systems (CISS), particularly the reliance on centralized logging and change verification mechanisms. This reduces audit transparency, complicates the evidential value of incidents, and creates regulatory risks in personal data protection. Purpose. To develop and substantiate a scientific and methodological approach for integrating permissioned blockchain technology into CISS of state registers to enhance resistance to insider actions, ensure transparency of access control, and increase trust in electronic public services. Methods. The study applies a systems analysis of CISS architectures and regulatory requirements, mathematical modeling of data flows, and experimental modeling in a virtualized environment using Hyperledger Fabric as a decentralized logging and verification module. Zero-Knowledge Proofs were applied to preserve transaction confidentiality, and behavioral analytics based on machine learning algorithms were used to detect anomalous activity. Results. A hybrid architecture was proposed in which traditional mechanisms of authentication, access control, and cryptographic protection are reinforced by a distributed event log and consensus-based verification of operations. This integration ensures data immutability and reproducibility of access history, reduces the possibility of hidden record editing by administrators, accelerates the detection of atypical user behavior, and creates a reliable evidential base for auditing. The proposed architecture complies with ISO/IEC 27001 requirements and supports data minimization and accountability principles, facilitating GDPR compliance during personal data processing. Conclusions. Integrating permissioned blockchain into CISS of state registers establishes a new level of trust and controllability of security: it increases audit transparency, mitigates insider risks, and preserves transaction confidentiality. The proposed approach is scalable and suitable for national e-government platforms and interagency data exchange systems.
As crypto exchanges and decentralized exchanges have proven untrustworthy, this paper seeks to create a rigorous Blockchain Project Evaluation Model (BPEM) for assessing the trustworthiness of a blockchain project. This BPEM will collate the components of technical audit, on-chain and off-chain analytics, liquidity indicators, and behavioral indicators into a single score of the project. The relevance of this work is driven by widespread instances of trade volume manipulation, opaque tokenomics, and tightening regulatory requirements (including in the context of MiCA). The scientific novelty lies in the creation of a hybrid MCDM architecture with an automated Incongruity Detection System (IDS) module that cross-checks tokenomics, liquidity, on-chain activity, and public statements and introduces a penalty coefficient into the final rating. The results of BPEM validation across case studies of wash trading and hidden centralization demonstrate that the key indicators of project resilience are not nominal volume but market depth, liquidity quality, and the integrity of on-chain data, and that identified inconsistencies act as early markers of scam projects and systemic risks. It is shown that a comprehensive multifactor analysis significantly outperforms the use of isolated metrics and can serve as a backbone for listing and compliance procedures. The article is of practical value for researchers of decentralized finance, risk managers, crypto exchange analysts, and digital asset regulators.
The design of financial instruments and processes is contingent on the infrastructure supporting them. Blockchain technology, as utilised by public crypto networks such as Ethereum, represents a novel type of payment and settlement infrastructure that gives rise to a new generation of solutions. This paper discusses the key properties of this technology, including immediacy, omni-asset capability, programmability and its ability to flatten the financial architecture (disintermediation). We illustrate the distinctive products these features make possible, and have the potential to disrupt current payment and capital market systems. We discuss the utility of blockchain technology in private (permissioned) networks. Finally, we revisit the risks of public crypto networks and their mitigants. This article is also included in the Business & Management Collection which can be accessed at https://hstalks.com/business/.
Данная работа посвящена исследованию вопроса обеспечения целостности производственной информации в окружении высокой автоматизации с помощью блокчейн-технологии. Задачи, которые решались в ходе исследования: 1. Исследование вопроса применения блокчейн-оракулов в промышленности для обеспечения целостности данных. 2. Разработка архитектуры соответствующего решения для промышленных производств. 3. Разработка модульной структуры в виде программного кода и рекомендаций по его встраиванию в промышленное цифровое окружение. Работа была проведена на основе открытых данных о блокчейне и средствах обеспечения безопасности информации в промышленности в условиях автоматизированного производства. Был произведен теоретический обзор вопроса и изучение самой технологии блокчейн, как и рассмотрение уже существующих примеров в качестве части комплексных решений формата «умный завод». Были рассмотрены инструменты и внешние сервисы, позволяющие развернуть подобную структуру обеспечения безопасности и целостности информации без использования сторонних комплексных решений «из коробки». В результате была разработана архитектура системы с блокчейн-оракулом, обеспечивающим логирование всех производственных данных в блокчейн-сеть Polygon с возможностью использования как открытой сети, так и развертывания собственной, закрытой от сети Интернет. Были разработаны модули, доступные для встраивания в любую автоматизированную архитектуру, и даны рекомендации по дальнейшей доработке в зависимости от нужд предприятия. Для достижения данных результатов в результате были использованы следующие информационные технологии: Python, web3.py, Solidity, Ethereum, Polygon.
Open access
Economic and Technological Systems Analysis
Aerospace, Electronics, Mathematical Modeling
Advanced Theoretical and Applied Studies in Material Sciences and Geometry
The article addresses the scientific problem of forming an efficient approach to assessing the market value of business projects in the rapidly evolving area of decentralized finance (DeFi) within the digital economy. The article analyzes the limitations of applying traditional financial evaluation methods, specifically discounted cash flow (DCF) models and economic value added (EVA), which lose their relevance in the DeFi context due to the instability of cash flows, absence of centralized reporting, and the specific profitability structure of tokenized assets. In order to overcome the mentioned limitations in the study, a new multifactor model has been proposed, which combines classical financial indicators with key tokenomic metrics: total value locked (TVL), the utility function of the token in governance, liquidity mining incentives, as well as the distribution of tokens over time (vesting schedules). An empirical validation of the model’s efficiency was conducted through the construction of a multiple linear regression based on data from 20 leading DeFi projects for the years 2023–2024. The results obtained demonstrated a high statistical significance of the included tokenomic variables (p < 0.01) and a high explanatory power of the model (R? = 0.92), confirming its efficiency for predicting the market capitalization of digital assets. It is demonstrated that tokenomic characteristics have a decisive impact on the value of DeFi projects, while traditional indicators (DCF, EVA) are secondary or insignificant due to the changing nature of value in the Web3 economy. The proposed model enables the development of a sound methodology for the strategic analysis of investment attractiveness of decentralized platforms, particularly from the perspective of DAO organizations, venture funds, and analytical agencies.
Андрій Олександрович Гашко, Андрій Петрович Бондарчук, Максим Петрович Трембовецький, Олександр Ілліч Чумак
The article examines an automated method for verifying the correctness of smart contracts in the Solana blockchain network. The relevance of the research is driven by the growing popularity of Web3 applications and the need to ensure their security, as even minor errors in smart contract code can lead to significant financial losses. The primary goal is to develop an automated verification methodology for smart contracts that can detect vulnerabilities such as the absence of founder rights verification, arithmetic operation errors, and missing transaction check signatures. Using static analysis techniques in the Rust programming language, the authors propose an approach that enables rapid analysis-taking less than three minutes per contract-and automatic generation of reports on identified vulnerabilities. The methodology is based on analyzing external data flows through smart contracts, allowing for the early detection of potential threats. To automate the process, Python and Bash scripts are employed, integrating with cloud services such as Amazon Web Services to scale the analysis. Testing results on real Web3 applications demonstrate the effectiveness of the methodology, particularly in reducing analysis time and improving the accuracy of error detection. An important aspect of the research is the continuous updating of knowledge bases and analysis tools, enabling the consideration of new types of attacks and vulnerabilities. The article also highlights the importance of interoperability between different blockchain networks, which remains a challenging task but is a key element for the future development of Web3. The research results show that the proposed methodology is promising for scaling and adapting to new challenges in blockchain ecosystems such as Solana. Thus, the developed approach to automated smart contract verification not only enhances the security of Web3 applications but also contributes to their further development, ensuring stability and reliability in the dynamic evolution of blockchain technologies.
Incorporating blockchain technology into vehicle classification systems shows potential progress in data security, transparency, and decentralization. This work examines how blockchain technology can improve vehicle classification procedures, emphasizing the advantages and hurdles of various consensus mechanisms. Conventional methods of categorizing vehicles typically depend on centralized databases susceptible to data tampering and breaches. Using blockchain ensures data integrity by utilizing decentralized and immutable ledgers. We assess different consensus algorithms such as Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Practical Byzantine Fault Tolerance (PBFT), Federated Byzantine Agreement (FBA), and DAG (Directed Acyclic Graph) to determine their appropriateness for vehicle categorization. Our aim is to determine the most effective and secure method for incorporating blockchain technology into vehicle classification systems by analyzing these consensus mechanisms.
The article examines the use of blockchain distributed ledger technology in various sectors of the economy. It was found that since 2008, blockchain has developed as a tool for cryptocurrency transactions and was later adopted by major transport companies for cargo transportation management, proving its efficiency. The study is based on general scientific methods of cognition, including the dialectical method for understanding phenomena and the comparative legal method for analyzing approaches to the legal nature of distributed ledger technology. Using a systemic-structural approach, the author examined the benefits and risks of digitalization and blockchain application, leading to the article's conclusions. Blockchain is applied in IT, energy, finance, agriculture, logistics, and other sectors, improving efficiency and transparency in business processes. However, Ukraine lacks legislative regulation of this technology. If implemented, blockchain could become a tool for promoting transparent business practices, reducing risks, and minimizing interference from government authorities.
The article explores an approach to implementing modern digital technologies, such as blockchain solutions, in the public finance management system, considering global experience. The purpose of the article is to develop recommendations for the implementation of digital technologies into the existing public finance management mechanism of modern Ukraine to reduce objective risks from the “human factor” in corporate and public management, and, in accordance with the goal, 5 research tasks are set and solved in the article. The author analyzes key challenges in public finance management, particularly the negative impact of the human factor, and proposes solutions aimed at minimizing errors, enhancing transparency, and reducing corruption risks. Existing methodologies and frameworks for evaluating digital technologies, such as the digital maturity models of the OECD, the World Bank, ISO 37122, as well as methodologies from NIST and the EU, are examined. The study develops a new methodological approach to the comprehensive evaluation of technologies, encompassing six key criteria: process automation, transparency, security, decentralization, efficiency, and implementation cost. A technology assessment system is proposed for each criterion, along with a mathematical model for calculating an integrated indicator. This methodology enables the classification of technologies as either key or auxiliary in the context of the digital transformation of the public finance management mechanism. The article emphasizes the unique potential of decentralized technologies, such as blockchain, in minimizing the impact of the human factor. The primary contribution of the study lies in creating a scientific basis for enhancing the efficiency of public administration by introducing modern digital technologies capable of minimizing the adverse effects of the human factor. Applying the developed technology evaluation methodology will provide a well-founded means to identify priority areas for the digital transformation of Ukraine’s public finance management system, taking into account global experience and national specifics.
With the development of digital technologies, smart contracts are becoming an important tool for improving social networks. The research examines the integration of smart contracts for intelligent data analysis and process automation. These self-executing blockchain-based applications could revolutionize the way data management, content monetization, and user engagement are approached. The developed system provides automation of transactions, payments to authors, protection of personal data and decision-making in communities. This makes it possible to monitor user interaction in real time and analyze their activity, automatically recording and processing data without the intervention of intermediaries. This approach provides high transparency and accuracy, which makes it effective for researching social trends, identifying public opinion leaders, and evaluating content impact. Smart contracts also help streamline processes that previously required human intervention, keeping all actions and transactions stored on the blockchain transparent. This increases user trust and creates a fairer environment for interaction on the platform. Therefore, the developed system includes several technological aspects, such as blockchain, smart contracts, intelligent data analysis, as well as the integration of these technologies in social networks
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
This work is devoted to the research of the blockchain network, in particular, aimed at detecting illegal activity in the Ethereum network using forensic methods. The paper describes the concepts and basic vulnerabilities related to the Ethereum network and the integration of graph analysis to develop an algorithm that scrutinizes Ethereum's transaction structure for illegal activities, including money laundering. In addition, the study includes an analysis of the very structure of Ethereum and the blockchain, which allows insight into the identification and analysis of various aspects of their functioning. The research results are used for the software implementation of the study and improvement of the security level of the blockchain network, including the creation of advanced software solutions for network analysis and protection of the integrity of the blockchain ecosystem. This integrated methodology aims to protect the integrity of blockchain ecosystems.
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing