The paper proposes an extended quality assessment model for Distributed Ledger Technology platforms, referred to as DLT-QM, developed on the basis of the ISO/IEC 25010 standard while considering the architectural and operational specifics of decentralized and blockchain-based systems. The relevance of the study is determined by the rapid development of digital technologies and the growing adoption of DLT platforms in finance, e-government, logistics, IoT ecosystems, and enterprise information systems, alongside the absence of a unified formalized approach for comprehensive quality assessment of such platforms. The study analyzes the applicability of ISO/IEC 25010 charac-teristics to DLT-oriented software systems and identifies a set of DLT-specific quality attributes reflecting the unique properties of distributed ledger environments, including decentralization level, consensus reliability, transaction finality, auditability, trust model, interoperability, and on-chain/off-chain balance. For each characteristic, mathematical metrics are formalized to support multicriteria quality assessment and optimization of architectural decisions in software engineering tasks. The integral quality indicator QDLT is defined as a weighted combination of the traditional ISO/IEC 25010 component and a DLT-specific component, enabling the adaptation of the model to various application scenarios. The proposed model is validated using four representative DLT platforms: Hyperledger Fabric, Ethereum, Corda, and Polygon. The obtained results confirm the existence of structural trade-offs between decentralization, performance, security, and interoperability in modern distributed systems. Furthermore, a scenario-oriented application methodology is developed, including a procedure for determining weighting coefficients depending on the application domain, such as financial consortium systems, e-government infrastructures, and IoT supply chain environments. The practical significance of the research lies in the development of a formalized decision-support instrument for selecting DLT platforms in the design and implementation of modern software systems and digital services. Keywords: blockchain, distributed ledger technology, DLT platforms, decentralized systems, distributed systems, information technologies, digital technologies, software engineering.
Юлія Гусєва, Ігор Чумаченко, Іван Некрасов, Ілля Худяков · 5 authors
The subject of this study is the processes of ensuring transparency, accountability, and data integrity in project portfolio management systems based on distributed ledger technologies. The objective of this work is to develop a conceptual model, the Blockchain Portfolio Governance Model (BPGM), to enhance the transparency, integrity, and manageability of strategic portfolio management processes. Objectives: to develop a multi-level model architecture that combines traditional management cycles with cryptographic event logging mechanisms; to formalize management decisions as distributed ledger objects using asymmetric cryptography; to propose a comprehensive management quality assessment metric that accounts for both technical integrity and procedural discipline; to validate the model through simulation modeling of business processes. Research methods: systems analysis, methods of mathematical and simulation modeling in the Bizagi Modeler environment, asymmetric encryption, and hashing algorithms to ensure data integrity in distributed networks. Results. This paper proposes and justifies the architecture of the Blockchain Portfolio Governance Model, comprising five levels: governance, data aggregation, decision formalization, cryptographic integrity, and audit. A mathematical framework for event logging has been developed, where each decision is signed using the ECDSA digital signature algorithm. A new comprehensive metric has been introduced – the Portfolio Governance Compliance Index – which enables the detection of "shadow" management actions by comparing the number of requests initiated in external systems with the number of validated transactions on the blockchain. A series of simulation experiments demonstrated that implementing Proof-of-Authority consensus algorithms in a corporate network introduces negligible time delays (less than 1% of the total cycle), while the majority of the process time is spent on expert analysis. Conclusions: The application of the BPGM model enables transforming subjective portfolio management into a transparent, algorithmic process. The proposed solution ensures the creation of a «single source of truth» for all stakeholders, significantly simplifies audit procedures, and enhances the organization’s institutional reliability without compromising its operational efficiency.
Yuliia Husieva, Igor Chumachenkо, I. B. Nekrasov, Illia Khudiakov · 5 authors
The subject of this study is the processes of ensuring transparency, accountability, and data integrity in project portfolio management systems based on distributed ledger technologies. The objective of this work is to develop a conceptual model, the Blockchain Portfolio Governance Model (BPGM), to enhance the transparency, integrity, and manageability of strategic portfolio management processes. Objectives: to develop a multi-level model architecture that combines traditional management cycles with cryptographic event logging mechanisms; to formalize management decisions as distributed ledger objects using asymmetric cryptography; to propose a comprehensive management quality assessment metric that accounts for both technical integrity and procedural discipline; to validate the model through simulation modeling of business processes. Research methods: systems analysis, methods of mathematical and simulation modeling in the Bizagi Modeler environment, asymmetric encryption, and hashing algorithms to ensure data integrity in distributed networks. Results. This paper proposes and justifies the architecture of the Blockchain Portfolio Governance Model, comprising five levels: governance, data aggregation, decision formalization, cryptographic integrity, and audit. A mathematical framework for event logging has been developed, where each decision is signed using the ECDSA digital signature algorithm. A new comprehensive metric has been introduced – the Portfolio Governance Compliance Index – which enables the detection of "shadow" management actions by comparing the number of requests initiated in external systems with the number of validated transactions on the blockchain. A series of simulation experiments demonstrated that implementing Proof-of-Authority consensus algorithms in a corporate network introduces negligible time delays (less than 1% of the total cycle), while the majority of the process time is spent on expert analysis. Conclusions: The application of the BPGM model enables transforming subjective portfolio management into a transparent, algorithmic process. The proposed solution ensures the creation of a «single source of truth» for all stakeholders, significantly simplifies audit procedures, and enhances the organization’s institutional reliability without compromising its operational efficiency.
This paper develops a document management system model intended for environments in which the integrity of document history, control of the document lifecycle, and the possibility of independent verification of performed operations are critically important. The relevance of the study is determined by the fact that traditional electronic document management systems mainly rely on centralized event logs and application logic, which does not eliminate the risks of retrospective modification of document history and a reduction in its evidential value. The aim of the work is to construct a document management system model in which the integrity of document history is ensured through a cryptographically verifiable chain of document states and the recording of evidential event attributes in a permissioned distributed ledger. The proposed model combines architectural and formal levels of system representation. At the architectural level, the user, application, evidential, and content layers are distinguished. At the formal level, a document is represented as a sequence of cryptographically linked states, in which each new state contains the state hash, metadata, timestamp, content hash, and a reference to the previous state, thus ensuring the integrity and traceability of the entire document history. To implement the evidential layer, a smart contract for registering document states and a permissioned distributed ledger based on Hyperledger Besu are used. Experimental validation of the model was carried out on a local testbed using the QBFT consensus mechanism, external storage, and software modules for generating and fully verifying document history. The experimental results confirmed the ability of the model to detect retrospective changes in content, metadata, signatures, and temporal attributes, to localize the first compromised state, and to provide near-linear growth in full verification time as the length of the state chain increases. Comparative evaluation against centralized logging demonstrated the advantage of the proposed approach in terms of tamper detection, localization of violations, and independent verifiability of results. The practical significance of the work lies in the possibility of using the proposed model as a basis for building corporate document management systems.
Євген Олександрович Живило, Юрій Володимирович Кучма
Formulation of the problem in general. The purpose of the article is to develop a multi-agent model of adaptive trust for decentralised confidential systems, capable of ensuring the integrity and reliability of computing processes in the presence of adaptive attacks on network nodes. Research methods. During the research, analysis and synthesis methods were used to study approaches to the construction of multi-agent systems and trust management mechanisms in decentralised environments. The method of system and simulation modelling was used to develop a multi-agent model of adaptive trust and to study its behaviour under attacks on the integrity of computing processes. Experimental and comparative methods enabled evaluation of the proposed approach's effectiveness and justification of its advantages over static trust models. Literature review. Literary analysis shows that modern models of trust in decentralised systems are based on the integration of dynamic adaptive mechanisms, AI algorithms, and cryptographic protocols, which allow for increased cyber resilience and data integrity. At the same time, questions remain open about the scalability of models, the optimisation of adaptation parameters, and the integration of national and European regulatory approaches into practical systems, which provide a scientific perspective for the development of multi-agent models of adaptive trust. Research results. The article formalises attacks on the integrity of computing processes and develops a multi-agent model of adaptive trust for decentralised confidential systems based on Bayesian updating and evolutionary adaptation of strategies. The results of the simulation experiments confirmed that the proposed model provides high resistance to attacks, rapid stabilisation of agent confidence levels and an effective balance between security, privacy and performance. Research novelty. The work improves approaches to trust formation in decentralised systems by integrating models of multi-agent interaction and stochastic game theory, in which trust is modelled as an evolutionary process under conditions of incomplete information. Well-known Bayesian models of trust have been expanded by combining Bayesian belief update mechanisms with reinforcement learning algorithms, ensuring dynamic adaptation of agent behaviour to variable and targeted attacks on the integrity of computational processes. The mechanism for correcting agents' strategies has been clarified, extending classic game models of trust to decentralised, confidential systems without centralised control, thereby increasing their resistance to adaptive threats. Theoretical and practical significance. The study expands theoretical approaches to the formation of adaptive trust in decentralised systems and integrates Bayesian updating with reinforcement learning algorithms. In practice, the model increases resistance to integrity attacks and ensures the confidentiality of data exchange, enabling the adaptive development of secure platforms for federated learning, Web3, and IoT. Conclusion and future work. The proposed model of adaptive trust in decentralised systems, integrating Bayesian updating, behavioural indicators, and reinforcement learning, ensures agent self-adaptation and increases resistance to attacks on data integrity under conditions of incomplete information. Simulation experiments confirmed the model's effectiveness in balancing security, privacy, and the transparency of interaction, opening the way for integration into Zero Trust Architecture and the development of intelligent, next-generation trust systems.
This thesis deals with the implementation of a system for acquiring and processing transactions from various cryptocurrency blockchains. The aim of the thesis is to design and implement a system as a library that provides a unified interface for working with multiple blockchain networks. A key feature of the proposed system is its modularity, which enables future expansion to support additional cryptocurrencies. The thesis describes the architecture of selected blockchains and analyzes existing methods of obtaining data from these networks. Based on an analysis of available tools, Tatum.io was chosen as a suitable platform, as it offers interfaces for communication with a large number of blockchains. Subsequently, a general library model with an adapter-type architecture was designed, where each adapter ensures communication with a specific blockchain. The implementation was carried out in the Typescript language. The resulting library allows the user to track transactions based on specified parameters, which are: tracked address, time range (or block range), and blockchain type. The contribution of this work is the creation of a universal interface between the user and various blockchains without the need for detailed knowledge of them.
The paper investigates the issues of secure functioning of a two-level blockchain with a complex mixed consensus protocol — Proof-of-Work in the main blockchain (mainchain) and Proof-of-Stake in the secondary (sidechain). The principle of building such a blockchain is based on the Proof-of-Proof protocol, where a stable blockchain (mainchain) is used to ensure the stability of the sidechain, by referring the mainchain blocks to the sidechain blocks using special transactions. Such a structure allows for faster block generation in the sidechain and, accordingly, faster processing of transactions without reducing stability and without increasing the block size. In turn, such a two-level blockchain is of the greatest interest for the creation of a cascade system of state registers, which will be guaranteed to be protected against the substitution and forgery of documents. The main results of the work areexplicit analytical expressions for estimates of the probability of double spend attack on such a two-level blockchain, under the condition of an adversary in the sidechain and in the mainchain. The expressions obtained allow finding the number of confirmation blocks in the sidechain, which guarantees security against the attack with a probability no less than a preset value. Keywords: blockchain, mainchain, sidechain, cryptocurrencies, mining, Proof-of-Proof consensus protocol, double spend attack.
Кваліфікаційна робота бакалавра складається зі вступу, чотирьох розділів, висновків, списку використаних джерел та додатків. У першому розділі виконано аналіз предметної області, наведено приклади існуючих рішень та визначено основні функціональні потреби користувачів. Другий розділ містить специфікацію функціональних і нефункціональних вимог до інформаційної системи, її логічну структуру та ключові компоненти. У третьому розділі було здійснено розробку вебзастосунку з підтримкою смарт-контрактів для безпечного виконання криптотранзакцій на базі бібліотеки React та мови програмування Solidity, доповнивши цей технологічний стек хмарною платформою Supabase та бібліотекою Ethers.js для взаємодії з криптогаманцем MetaMask. У четвертому розділі наведено спеціальні розрахунки, зокрема здійснено ергономічну оцінку функціональних компонентів програмного продукту з використанням математичних моделей, розраховано час на виконання повного циклу замовлення в Web3-системі з урахуванням мережевих затримок та фізичного введення даних, а також обґрунтовано високу ефективність спроєктованого інтерфейсу. У висновках узагальнено результати виконаної роботи та визначено перспективи подальшого розвитку системи.
In the modern context of information technology development, the management of labor processes in complex IT projects acquires the features of self-organization and dynamic adaptation. The article examines the principles of configuring agent interactions within the labor environment of IT projects as a tool for enhancing the efficiency of team management. The agent-based interaction model makes it possible to consider each team member as an autonomous agent capable of making decisions, adapting behavior to the task context, and interacting with other elements of the system within a distributed environment. Conceptual foundations have been developed for constructing the architecture of agent interactions, based on the principles of cognitive exchange, communicative coherence, flexible role distribution, and multilevel task management. It is determined that the key factor in the effectiveness of such interactions is the balance between agent autonomy and centralized process coordination. A systematic classification of agent configuration types is proposed: hierarchical, decentralized, hybrid, and cognitively adaptive, which differ in the level of information connectivity and the system’s response speed. The study also investigates the impact of cognitive factors on the dynamics of interactions between agents, such as trust, intellectual compatibility, role specialization, and the ability for collective learning. A model for assessing the effectiveness of agent interaction is proposed, using indicators of performance, informational transparency, decision synchronization level, and team adaptability index. It is established that the configuration of agent connections directly determines the speed of decision-making, the coherence of actions, and the level of project innovation activity. The results of the study have practical significance for building multi-agent IT team management systems, developing algorithms for adaptive resource allocation, and creating cognitive project management dashboards. The proposed principles can be used to optimize communication processes, reduce the risk of conflicts, and enhance the resilience of organizational structures under conditions of high labor environment complexity.
Open access
Information Systems and Technology Applications
Mathematical Control Systems and Analysis
Technology and Human Factors in Education and Health
In the modern context of information technology development, the management of labor processes in complex IT projects acquires the features of self-organization and dynamic adaptation. The article examines the principles of configuring agent interactions within the labor environment of IT projects as a tool for enhancing the efficiency of team management. The agent-based interaction model makes it possible to consider each team member as an autonomous agent capable of making decisions, adapting behavior to the task context, and interacting with other elements of the system within a distributed environment. Conceptual foundations have been developed for constructing the architecture of agent interactions, based on the principles of cognitive exchange, communicative coherence, flexible role distribution, and multilevel task management. It is determined that the key factor in the effectiveness of such interactions is the balance between agent autonomy and centralized process coordination. A systematic classification of agent configuration types is proposed: hierarchical, decentralized, hybrid, and cognitively adaptive, which differ in the level of information connectivity and the system’s response speed. The study also investigates the impact of cognitive factors on the dynamics of interactions between agents, such as trust, intellectual compatibility, role specialization, and the ability for collective learning. A model for assessing the effectiveness of agent interaction is proposed, using indicators of performance, informational transparency, decision synchronization level, and team adaptability index. It is established that the configuration of agent connections directly determines the speed of decision-making, the coherence of actions, and the level of project innovation activity. The results of the study have practical significance for building multi-agent IT team management systems, developing algorithms for adaptive resource allocation, and creating cognitive project management dashboards. The proposed principles can be used to optimize communication processes, reduce the risk of conflicts, and enhance the resilience of organizational structures under conditions of high labor environment complexity.
The article proposes a comprehensive approach to solving the data protection problem in decentralized distributed information storage systems based on blockchain technology. A conceptual "SecureChain" model has been developed that integrates modern cryptographic protection methods with programmable smart contract logic for automated access management and data integrity assurance. The model employs a multi-level architecture including data layer, smart contract layer, network interaction layer, and user interface. The key innovation is the application of Shamir's threshold encryption schemes (t, n) controlled by smart contracts, combination of symmetric and asymmetric encryption algorithms (AES-256 for data, Curve25519 for keys), and implementation of a "secret disclosure" mechanism to enhance critical information security. Experimental validation of the model was conducted in three typical use cases: medical data storage system, corporate document management system, and electronic voting platform. Results demonstrate significant improvement in key security metrics compared to traditional approaches: resistance to attacks on individual nodes (by 65%), data confidentiality (by 72%), access audit capability (by 90%), and fault tolerance (by 58%) with moderate increases in storage costs (by 15%) and access time (by 10%). Additional scalability analysis showed a near-linear relationship between performance and both data volume and number of users. The proposed model and implementation methodology have significant practical value for organizations working with confidential data and requiring reliable distributed storage systems that meet modern security requirements and regulatory standards. Keywords: smart contracts, cryptographic protection, threshold encryption, distributed systems, key management, data integrity, network security.
Просолов, Владислав Валерійович, Халімов, Геннадій Зайдулович, Шулік, Павло Вікторович, Смірнов, Антон Олександрович · 5 authors
The subject of the research is methods for detecting attacks in networks with the Proof-of-Stake (PoS) consensus mechanism. The purpose of this experimental investigation and analysis is to evaluate the effectiveness of classical machine learning algorithms for detecting malicious nodes in blockchain systems. The tasks include the analysis of blockchain technology vulnerabilities, the creation and use of a specialized dataset for PoS networks, as well as the construction and testing of machine learning models. The main focus is placed on comparing three algorithms – Random Forest, Support Vector Machine, and k-Nearest Neighbors – in order to determine their suitability for monitoring node activity and detecting anomalies. To solve the tasks set, the following methods were implemented: modeling, empirical, and mathematical approaches were applied. Modeling consisted of software implementation of the selected algorithms and subsequent analysis of their performance using accuracy, recall, F1-score metrics, and confusion matrices. Empirical methods were realized through testing the models on a partially synthetic dataset containing more than 10,000 records of blockchain nodes and transactions. Mathematical methods involved the calculation of statistical performance indicators and the analysis of feature importance that characterizes node behavior. The achieved results include the validation of a dataset for PoS blockchains that incorporates key operational parameters of transactions and nodes, the development of recommendations for further use of machine learning models, and the testing of selected models. Conclusions. The study demonstrated that machine learning is an effective tool for identifying anomalies and malicious activity in blockchain systems. The obtained results lay the foundation for further research, which may focus on expanding the feature space, integrating deep neural networks, developing ensemble approaches, and adapting methods to different types of blockchains.
The subject of the research is methods for detecting attacks in networks with the Proof-of-Stake (PoS) consensus mechanism. The purpose of this experimental investigation and analysis is to evaluate the effectiveness of classical machine learning algorithms for detecting malicious nodes in blockchain systems. The tasks include the analysis of blockchain technology vulnerabilities, the creation and use of a specialized dataset for PoS networks, as well as the construction and testing of machine learning models. The main focus is placed on comparing three algorithms – Random Forest, Support Vector Machine, and k-Nearest Neighbors – in order to determine their suitability for monitoring node activity and detecting anomalies. To solve the tasks set, the following methods were implemented: modeling, empirical, and mathematical approaches were applied. Modeling consisted of software implementation of the selected algorithms and subsequent analysis of their performance using accuracy, recall, F1-score metrics, and confusion matrices. Empirical methods were realized through testing the models on a partially synthetic dataset containing more than 10,000 records of blockchain nodes and transactions. Mathematical methods involved the calculation of statistical performance indicators and the analysis of feature importance that characterizes node behavior. The achieved results include the validation of a dataset for PoS blockchains that incorporates key operational parameters of transactions and nodes, the development of recommendations for further use of machine learning models, and the testing of selected models. Conclusions. The study demonstrated that machine learning is an effective tool for identifying anomalies and malicious activity in blockchain systems. The obtained results lay the foundation for further research, which may focus on expanding the feature space, integrating deep neural networks, developing ensemble approaches, and adapting methods to different types of blockchains.
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
Research in the field of integrating biometric technologies with distributed ledger technologies, particularly with blockchain technology, aims to find ways to enhance security, privacy, and functional compatibility in the design of modern hybrid biometric systems. Biometric and blockchain technologies each have their own advantages and potential independently of each other. Their integration allows for the mutually beneficial use of these advantages. This article is dedicated to various aspects of the integration of biometric and blockchain technologies. It discusses the use of biometric systems at the level of identity management and access control in blockchain, especially the development and use of biometric digital signatures. It also examines the application of blockchain in managing biometric data, particularly the secure storage of biometric templates in blockchain
Open access
Advanced Research in Systems and Signal Processing
The nature of virtual assets and their legal regulation is a challenge for policymakers, because virtual assets themselves are a new phenomenon in the field of social and economic relations, which is significantly different from established types of property. The market of virtual assets, which has achieved significant development over the past 10 years, is of interest for research and from a fiscal point of view, because despite its significant volume, agreed approaches to the taxation of operations carried out in such a market are absent or are at the stage of development. A significant number of new challenges facing the legislator when determining the tax regime of operations with virtual assets arise from their qualities, which are categorically different from other types of assets. Virtual assets have a significant number of subspecies, which on the one hand are significantly different from each other, and on the other hand share common features. In particular, the most famous virtual assets - Bitcoin, Ethereum are completely decentralized, do not have a specific issuer, do not certify any civil rights of the owner, and do not have security. On the other hand, such types of virtual assets as electronic money tokens («stablecoins») or tokens related to assets are a form of expression of civil rights, namely the rights of claim against the issuer. Thus, it is problematic to determine which set of characteristics to use to distinguish virtual assets from other types of property while taking into account the full range of diversity of virtual assets themselves. In addition, transactions with virtual assets take place in forms different from transactions with cash, securities, etc. The ability of subjects to store, exchange, acquire and alienate virtual assets without the participation of any financial institutions or other intermediaries is another challenge in rulemaking, because it complicates the application of existing control methods in the field of taxation. A separate category of problems is also the phenomenon of decentralized finance («DeFi»), which eliminates intermediaries not only from the basic operations of moving virtual assets, but also from more complex economic operations, such as credit activities, loans, collateral, derivative contracts, etc. Considering the above, the relevance of the research lies in the emergence of qualitatively new categories of social relations, which, like any other social and economic relations, require legal regulation. Currently available regulatory instruments are not able to fully cover all the variety of operations with virtual assets, and to provide appropriate, special regulation of them.
This article provides a comprehensive analysis of the key risks associated with the operation of a crypto platform in the context of the transition to Web3 technology. The authors explore the activities of leading blockchain platforms such as Ethereum, Solana, Binance Smart Chain, Polkadot, Avalanche, Cosmos and Polygon, identifying the main types of risks that apply to the implementation of Web3 technology. The paper identifies threats associated with cryptocurrency volatility, regulatory uncertainty, cybersecurity, specific risks of decentralized finance (DeFi) and non-fungible tokens (NFTs), as well as scalability, accessibility and environmental issues. The authors analyzed the activities of the crypto platform and found that each platform has a unique structure and asset structure, which affects the nature of the risks. For example, Ethereum dominates the DeFi and NFT sectors, Solana is distinguished by its speed and low fees, Binance Smart Chain focuses on DeFi, and Polkadot and Cosmos are developing cross-chain technologies for interoperability. The main risks analyzed in the article include: Volatility of cryptocurrencies, which can increase financial instability; Cybersecurity, including hacking attacks and vulnerabilities of smart contracts; Regulatory uncertainty, which can hinder innovation and create legal conflicts; DeFi risks, such as errors in smart contracts, liquidation problems and systemic failures; NFT risks, in particular high market speculation and fraud risks; Scalability, including technical limitations and high fees; Complexity of use, which can limit the widespread adoption of Web3; Accessibility and inclusiveness, including unequal access to technologies; Energy consumption and environmental friendliness, which can affect the environment. To minimize these risks, the authors proposed a risk management strategy based on semi-fundamental principles: comprehensiveness, preventiveness, consistency, decentralization, transparency, security and interoperability. This strategy includes the introduction of modern analytical methods such as scenario analysis, machine learning, Value at Risk (VaR), Conditional VaR (CVaR), Monte Carlo models, multi-level security systems, bug bounty programs, transaction encryption, decentralized oracles, risk hedging using derivatives and RegTech solutions for regulatory compliance. For the effective implementation of the proposed strategy, a risk management roadmap was developed, which details the stages of risk identification, assessment, management and monitoring. This map includes specific tools for each stage, such as scenario analysis, AI analytics, blockchain scanners, VaR and CVaR models, attack models, stress testing, blockchain analytics, encryption, futures, options, RegTech, KPIs and behavioral models. The implementation of the proposed strategy will create a favorable environment for the reliable and sustainable development of Web3 technologies and the cryptocurrency market. Further research should be aimed at detailing platform-specific strategies and adapting them to the changing landscape of Web3.
Andreas Vlachos, Klitos Christodoulou, Elias Iosif, Marinos Themistocleous
Since 2009 cryptocurrencies have been adopted by many stakeholders worldwide. At the time, the market capitalization of cryptocurrencies exceeded 2.5 trillion US dollars and is expected to grow even more in the next few years. Despite the cryptocurrency disruption in numerous sectors, there is no common legal framework that is used worldwide. Currently, there is a variation of different legal and regulatory frameworks used across different countries. The assessment of these frameworks is time-consuming and subjective as it is done manually. There is, therefore, a need for tools that can assess the regulatory landscape of cryptocurrencies and blockchain tokens across different countries in a more efficient and objective manner. This chapter investigates this area and proposes an algorithmic model to assess this rapidly evolving landscape. The model is tested using empirical data collected from 194 countries using web mining. The proposed algorithmic model contributes to the body of knowledge and provides stakeholders with a systematic and scalable approach to evaluate regulatory environments.
Пояснювальна записка дипломного проєкту складається з п’яти розділів, містить 37 таблиць, 24 рисунки та 28 джерел – загалом 86 сторінок. Дипломний проєкт присвячений розробці веб-застосунку для зберігання та верифікації автентичності цифрових документів з використанням смарт-контрактів в мережі Ethereum. У роботі реалізовано безпечне збереження криптографічних хешів документів у блокчейні, що забезпечує незмінність даних та прозору перевірку без залучення довіреної сторони. Для безпечного оновлення контрактної логіки впроваджено проксі-патерн UUPS з контролем доступу через мультипідписний гаманець (Gnosis Safe). Комунікація між мікросервісами організована через Apache Kafka. Мета проєкту — створення децентралізованої системи перевірки достовірності документів, яка поєднує переваги блокчейн-технологій із зручністю класичного веб-інтерфейсу. У першому розділі розглянуто аналіз предметної області, існуючих рішень, моделей зберігання та перевірки цифрових документів. Другий розділ присвячений визначенню вимог до програмного забезпечення, моделюванню бізнес-процесів, побудові діаграм варіантів використання та трасування вимог. У третьому розділі викладено архітектуру системи, структуру смарт-контрактів, класів та бази даних, описано використаний технологічний стек. Четвертий розділ присвячений опису реалізації основних алгоритмів, перевірки безпеки системи, структури контрактів та механізму верифікації. П’ятий розділ включає оцінку результатів, висновки та рекомендації щодо подальшого розвитку проєкту. Програмне забезпечення впроваджено в мережі Ethereum Sepolia, з використанням Infura, PostgreSQL та Spring Boot.
Current directions of development of information and communication technologies and control tools 114 ПРОБЛЕМНІ ПИТАННЯ ЗАСТОСУВАННЯ ГОМОМОРФНОГО ШИФРУВАННЯ Гущин Б.-Д.І.Харківський національний університет радіоелектроніки, Харків, Україна Гомоморфне шифрування (Homomorphic Encryption, HE) -технологія, що дозволяє виконувати обчислення над зашифрованими даними без їх розшифрування [1-3].Застосування гомоморфного шифрування відкриває великі можливості для обробки зашифрованих даних без їх розшифрування в багатьох сферах, де критично важливо зберігати конфіденційність інформації.. Однак, попри потенціал, існує низка проблемних питань, які стримують широке впровадження цієї технології в практичні системи безпеки та обробки даних.Метою доповіді є аналіз проблемних питань при практичному застосуванні гомоморфного шифрування.В роботі розглянуті ключові сучасні сфери застосування HE [1-3].1. Хмарні обчислення (Cloud Computing), обробка зашифрованих даних на стороні постачальника хмарних послуг без розкриття вмісту.2. В медицині та біоінформатиці захищене зберігання та аналіз медичних записів пацієнтів, генетичної інформації (DНК).Використання HE у дослідженнях із багатьма організаціями без обміну розшифрованими даними.3. В фінансових сервісах конфіденційна аналітика для банків, страхових компаній, бірж.Обчислення кредитного рейтингу, оцінка ризиків без доступу до відкритих даних клієнта. Електронне голосування (E-voting).Забезпечення анонімності та перевірності результатів голосування, так як дані не розкриваються, але можуть бути агреговані без розшифрування.5. В Інтернеті речей (IoT) для обробки конфіденційних даних, зібраних з розумних пристроїв, безпосередньо на сервері або у хмарі.Використання в промисловому IoT (IIoT), медичних пристроях, Smart City.6. Захист персональних даних у Big Data, аналітика зашифрованих великих масивів даних з соціальних мереж, телекомів, сервісів для обчислення трендів, поведінкових моделей, не розкриваючи особистості.7. Машинне навчання над зашифрованими даними (Privacy-Preserving ML).Навчання або інференс моделей на даних, які ніколи не розшифровуються.Використання в конфіденційній медичній діагностиці, рекомендаційних системах, фінансах.Працює разом з Federated Learning, Secure Multi-Party Computation (SMPC).8. В юридичних сервісах та державному управлінні для безпечної взаємодії між державними структурами при обробці реєстрів, митних даних, податкових баз, де важлива повна конфіденційність.9. В системах кібербезпеки та цифрової ідентичності.Застосовується в антифрод-системах, аналізі поведінки користувачів без втрати їхньої конфіденційності.Підтримка Zero Knowledge Proofs та протоколів автентифікації.
In this age of always-on connection, it is very important to keep data safe while also protecting user privacy. In today's networks, where data travels through many pathways, such as cloud services and IoT devices, cryptographic algorithms are very important for keeping private data safe. But it's still exceptionally difficult to create beyond any doubt that information is secure without putting people's protection at chance. This conversation goes into detail almost privacy-preserving security strategies, looking at their significance, issues, and other ways to solve them. The objective of privacy-preserving cryptographic strategies is to create beyond any doubt that private information is kept secure whereas still permitting secure contact and computation. To keep data secure from individuals who shouldn't have get to to it, these frameworks utilize diverse sorts of cryptography, like encryption, hashing, and secure multi-party computation (SMPC). Information spills and illicit observing are less likely to happen with these methods because they cover up information at diverse steps of exchange and handling. Indeed in spite of the fact that they may well be useful, privacy-preserving cryptographic strategies have a number of issues. Finding a great blend between client security and information security is one of the most issues. Extreme security measures may offer assistance keep information secure, but they frequently include collecting information in ways that are as well intrusive and abuse people's security. On the other hand, putting as well much accentuation on protection might make security weaker, taking off information open to being abused. Finding a cautious adjust between these competing objectives is key to making cryptographic frameworks that work well. A few potential methods that permit secure information taking care of whereas ensuring security are homomorphic encryption, differential protection, and zero-knowledge proofs. Improvements in hardware-accelerated cryptography and distributed computing tools also make it possible to speed up secure processes and make them more scalable.
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.
The emergence of blockchain technology has revolutionized various sectors by introducing decentralized and immutable ledgers. Ethereum, one of the leading blockchain platforms, has gained significant attention for its smart contract capabilities and ability to produce decentralized applications. Despite these innovative advancements, blockchain transaction networks, including Ethereum, have become a new space for the emergence of illegal activities from financial fraud to money laundering and terrorist financing. By combining theoretical knowledge with practical methodologies, this paper aims to contribute to the ongoing efforts to increase the security and transparency of blockchain networks, especially the Ethereum blockchain. The proposed methods leverage supervised machine learning, Financial Action Task Force (FATF) red flags and transaction graph visualization. Through the development and validation of innovative detection methods, the findings of this research are expected to enable stakeholders to proactively mitigate the risks associated with illicit transaction activities on the Ethereum blockchain.
This paper explores the integration of blockchain technology to enhance data integrity in cloud computing environments. As data breaches and unauthorized access continue to challenge traditional cloud security measures, blockchain offers a decentralized solution that ensures tamper-proof record-keeping and accountability. By leveraging cryptographic techniques and distributed ledger technology, the proposed framework enables secure data storage, sharing, and validation processes. This study highlights key use cases, potential challenges, and the overall impact of blockchain on improving trust and reliability in cloud computing, paving the way for more robust data integrity solutions in various applications across industries.