The integration of blockchain technology into decision support systems (DSS) represents a paradigm shift in how organizations approach data integrity, transparency, and collaborative decision-making processes.This research explores the fundamental mechanisms through which blockchain technology enhances traditional DSS architectures, focusing on distributed ledger capabilities, consensus mechanisms, and cryptographic security features.The study examines various implementation frameworks, analyzing their effectiveness in real-world applications across multiple industrial sectors including healthcare, supply chain management, and financial services.Through comprehensive analysis of existing blockchain-based DSS implementations, this paper identifies key advantages such as immutable data records, enhanced transparency, reduced intermediary costs, and improved stakeholder trust.The research methodology encompasses both theoretical framework development and empirical evaluation of blockchain-DSS integration models.Critical challenges including scalability limitations, energy consumption concerns, and regulatory compliance issues are thoroughly investigated.The findings reveal that while blockchain technology significantly improves data reliability and system transparency in DSS environments, implementation requires careful consideration of technical constraints and organizational readiness.Performance metrics demonstrate measurable improvements in decision accuracy, audit trail completeness, and stakeholder confidence levels.The study concludes with recommendations for optimal blockchain-DSS integration strategies, highlighting the importance of hybrid approaches that combine traditional centralized processing with distributed ledger benefits.Future research directions include investigation of quantum-resistant blockchain protocols and artificial intelligence integration within blockchain-based decision support frameworks.This work contributes to the growing body of knowledge on distributed systems applications in organizational decision-making processes.
Open access
Blockchain Technology Applications and Security
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
В статье рассматриваются алгоритмы консенсуса как основа функционирования криптовалютных и блокчейн-систем. Раскрывается их экономическая и технологическая сущность, проводится сравнительный анализ основных моделей – Proof-of-Work (PoW), Proof-of-Stake (PoS), Delegated Proof-of-Stake (DPoS), Practical Byzantine Fault Tolerance (PBFT) и гибридных решений. Выделяются их преимущества и недостатки, определяется область применения и перспективы развития в условиях необходимости повышения масштабируемости, энергоэффективности и устойчивости к кибератакам. Особое внимание уделяется проблеме «триилеммы блокчейна» и поиску оптимального баланса между безопасностью, децентрализацией и производительностью. Сделан вывод о важности гибридных моделей и инновационных протоколов в формировании будущей архитектуры децентрализованных финансов.
Godfrey Murairidzi Gotora, Eva Tsitsi Chigodo, Godfrey Benjamin Zulu, Mfula Eunice
Since the synthesis and evolution of the coding and blockchain technology with the self-executing commands, there is a sudden shift to the smart contract consumption patterns. In the global virtual commerce this phenomenon has been enormously increasingly day by day. This has been so based on the distinct, clear and strong advantageous characteristics mainly lies in security, transparency and its unique way of its decentralized automation nature. A large scope of transactions of this technology’s usage has been implemented in virtual and argumentative reality where codes create a lot of services such as games and commercial services amongst end users basically with no lawyers involved. However, despite its wide adoption intensifies, it renders no immune from the potential risks and uncertainty issues like any other software-based platforms. In generic terms every industry needs a regulatory way, which oversee or set red lines of boundaries in the form of structures, organizations and policies. In this context the code written and protocols which are executed automatically in systems aught also to be vetted in legal judiciary systems.
This research examines the application of Long Short-Term Memory (LSTM) neural networks for predicting cryptocurrency prices, with a focus on Bitcoin (BTC) and Ethereum (ETH), the two dominant digital assets with the highest market capitalization. The study addresses the critical challenge of accurately forecasting cryptocurrency price movements in highly volatile markets, which is essential for informed investment decision-making in the digital economy. The methodology employs LSTM models trained on historical closing price data from 2014 to 2024 for Bitcoin and from 2017 to 2024 for Ethereum, utilizing an 80:20 training-to-testing ratio. Results demonstrate exceptional predictive accuracy with R² values of 99.08% for Bitcoin and 97.44% for Ethereum, while MAPE values remained low at 1.8% and 1.9%, respectively. The study concludes that LSTM models effectively capture complex patterns in cryptocurrency price movements, providing reliable short-term forecasting capabilities and contributing valuable insights to the intersection of artificial intelligence and digital economy development.
Contemporary digital environments are supported by digital identities to enable secure access to, for example, governance, healthcare, and finance applications. Nevertheless, such centralized, lack of user control, noninteroperable identity systems are drawbacks of present identity systems. In this paper, we present a decentralized, privacy- preserving, and inter-operable identity model as part of a conceptual framework for the blockchain based approach on the above-mentioned problems. To enhance trust and compliance, the framework also utilises consent-based mechanisms, layered-architecture and self-sovereign principles. Real-world use cases are described to illustrate the utility of the model in real life applications such as cross-border identity verification, sharing of health data, and validation of educational credentials.
The rapid integration of blockchain, cryptocurrency, and Web3 technologies into digital banks and fintech operations has created an integrated environment blending traditional financial systems with decentralised elements. This paper introduces the CryptoNeo Threat Modelling Framework (CNTMF), a proposed framework designed to address the risks in these ecosystems, such as oracle manipulation and cross-chain exploits. CNTMF represents a proposed extension of established methodologies like STRIDE, OWASP Top 10, NIST frameworks, LINDDUN, and PASTA, while incorporating tailored components including Hybrid Layer Analysis, the CRYPTOQ mnemonic for cryptocurrency-specific risks, and an AI-Augmented Feedback Loop. Drawing on real-world data from 2025 incidents, CNTMF supports data-driven mitigation to reduce losses, which totalled approximately $2.47 billion in the first half of 2025 across 344 security events (CertiK via GlobeNewswire, 2025; Infosecurity Magazine, 2025). Its phases guide asset mapping, risk profiling, prioritisation, mitigation, and iterative feedback. This supports security against evolving risks like state-sponsored attacks.
The breakneck pace of digital transformation in sectors around the world have driven developments in cybersecurity, AI and cloud technology. But with great progress comes great responsibility, and with generating such evolution it gives rise to lots of issues when it comes to data privacy, system to system connectivity, leveraging knowledge and infrastructure scalability. This paper provides an integrated solution that can be harnessed to secure, operate and make digital ecosystems more agile, by amalgamating present day practices and technologies that many organizations face in their current environments across security, operation and agility when it comes to digitalization. It covers proactive cybersecurity approaches like DevSecOps and Zero Trust Architecture, AI based intelligent threat analysis and real-time automation, and cloud-native and edge computing models for scalable and resilient infrastructure. The study at the same time showcases advancements in data processing and encryption, legal compliance, providing enterprises with a roadmap toward safer, AI-infused and cloud supported infrastructure. By bringing these columns together, the research offers strategic recommendations for businesses wishing to future-proof their digital business as they negotiate an ever more volatile and risk-filled technology environment.
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
Существующие типовые модели аутентификации с использованием цифровых удостоверений носят абстрактный характер. Для конкретизации модели аутентификации с использованием цифровых удостоверений предлагаются: алгоритм эмиссии цифровых удостоверений; алгоритм аутентификации на основе доказательства с нулевым разглашением. Производится количественная оценка раскрытых данных удостоверений в результате: предложенного алгоритма аутентификации на основе доказательства с нулевым разглашением; аутентификации с полным раскрытием атрибутов; аутентификации с частичным раскрытием атрибутов. Полученные результаты оценок анализируются и делаются соответствующие выводы. Existing standard authentication models using digital credentials tend to be abstract. To refine the authentication model using digital credentials, the following are proposed: a digital credential issuance algorithm and an authentication algorithm based on zero-knowledge proof. A quantitative assessment is conducted on the amount of disclosed credential data resulting from the proposed zero-knowledge proof-based authentication algorithm, authentication with full attribute disclosure, and authentication with partial attribute disclosure. The assessment results are analyzed, and relevant conclusions are drawn.
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 development of high-load computing systems in modern information environments represents a critical aspect of technological progress, necessitating the creation of innovative approaches to cybersecurity. The increasing intensity of data exchange, the complexity of computational processes, and the growing number of interacting nodes pose significant challenges to traditional information security methods. Classical centralized security models are gradually losing their effectiveness due to the high risk of data processing center compromise, the vulnerability to denial-of-service (DDoS) attacks, unauthorized access, and system exploits. These risks emphasize the necessity of implementing decentralized security mechanisms that can withstand emerging cyber threats and ensure the reliability of high-load computing infrastructures. This article presents a conceptual approach to enhancing the cybersecurity of high-load computing systems through the integration of blockchain technology and smart contracts. A comprehensive analysis of current threats and risks inherent in such systems has been conducted, along with an investigation into the efficiency of smart contracts in user authentication, access control, data verification, and attack prevention. Particular attention is given to the advantages of decentralized security solutions, including the elimination of single points of failure, the enhancement of transparency in security processes, and the automation of control mechanisms. The study also evaluates the resilience of blockchain-based security frameworks in mitigating both internal and external cyber threats. The proposed architectural model leverages smart contracts for managing access to computing resources, verifying transaction integrity, and minimizing the impact of external threats. The analysis of recent research in blockchain technologies and their application in high-load environments provides insights into the feasibility and advantages of such an approach. By utilizing smart contracts, it becomes possible to automate security procedures, reduce reliance on centralized authentication servers, and ensure that system interactions remain tamper-proof and resistant to adversarial attacks. The research findings indicate that integrating smart contracts into high-load computing systems enhances cybersecurity by automating data verification processes, eliminating intermediaries in transactions, and strengthening resilience against attacks. Furthermore, the study outlines promising directions for future research, including the optimization of smart contract execution mechanisms to reduce computational overhead and the integration of blockchain-based solutions into hybrid security models that combine decentralized and centralized approaches. This approach offers a strategic pathway for developing robust, scalable, and resilient cybersecurity frameworks tailored to the needs of high-performance computing infrastructures.
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
The article examines methods and information technologies aimed at ensuring the secure integration of the Ethereum blockchain with Internet of Things (IoT) systems. The relevance of the study is driven by the rapid development of IoT, which is accompanied by increasing cybersecurity threats, including unauthorized data access, man-in-the-middle (MITM) attacks, device identifier spoofing, and the low transparency of centralized systems. The use of Ethereum blockchain technology, particularly smart contracts, opens new opportunities for creating decentralized security management models for IoT devices, enhancing trust levels, automating processes, and minimizing third-party interference risks. The “Problem statement” section outlines the key challenges in securing IoT networks, including the vulnerabilities of centralized solutions, limited computational resources of devices, and the need to develop autonomous access control systems. The “Analysis of Recent Research and Publications” section summarizes modern approaches to integrating Ethereum blockchain into the IoT field, including tokenized identification mechanisms, access control, and transaction processing using smart contracts. It is noted that leading researchers suggest Layer-2 solutions (state channels, zk-rollups, Plasma) aimed at reducing the load on the main blockchain and improving scalability. The aim of the article is to systematize modern methods of integrating the Ethereum blockchain with IoT and develop recommendations for their implementation, considering the limited resources of devices. The “Research results” section presents a secure IoT system architecture concept based on decentralized account management, local storage of cryptographic keys on devices, the use of optimized transaction signing algorithms, and the introduction of a hybrid data storage model based on IPFS. The proposed model minimizes the risk of unauthorized access, increases transparency in the interaction between IoT devices, and reduces computational resource costs. The “Conclusions and prospects for further research” section emphasizes that the implementation of the Ethereum blockchain in IoT promotes the development of secure decentralized platforms. However, it requires addressing issues such as energy consumption, transaction costs, and optimizing client applications for low-performance devices. Future research should focus on developing effective scalability tools, adapting smart contracts to IoT specifics, and improving integration with cloud computing platforms for storing large data sets.
One of the modern areas of blockchain technology application is the Internet of Things (IoT). An important component of blockchain technology is the consensus layer. It includes consensus protocols that are used to establish and maintain consensus, as well as to ensure network security, accuracy, and protection of the registry from unauthorized access. Currently, there are a large number of different consensus protocols, including those for blockchain-based IoT networks. Therefore, choosing the most suitable consensus protocol for a specific distributed ledger system, in particular, for an IoT blockchain solution, is an important task. The problem of optimal blockchain consensus mechanism selection in IoT networks can be considered a multi-criteria decision-making problem. This paper presents the step-by-step development of a conceptual model of a system of optimal consensus protocol selection for blockchain-based IoT networks. Following this step-by-step approach, the final goal is to transform the conceptual framework into a practical, adaptive, and efficient decision-making system for blockchain-based IoT networks. The obtained results can be useful for developers and researchers working in the field of blockchain technology and the Internet of Things and contribute to improving the efficiency and security of IoT networks.
Introduction. Blockchain technology has emerged as a transformative innovation in distributed computing, providing a secure, transparent, and decentralized mechanism for data management. Initially introduced as the backbone of cryptocurrencies, blockchain has expanded into various sectors, including finance, healthcare, supply chain management, and governance. However, despite its numerous advantages, blockchain faces significant challenges, including scalability, transaction speed, and energy consumption. This article presents a comprehensive analysis of blockchain technology, focusing on its classification, consensus mechanisms, scalability solutions, and future trends. The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. Purpose of the Work. The objective of this study is to conduct an in-depth analysis of blockchain technology, investigating its core principles, operational mechanisms, and performance optimization strategies. The research aims to provide a systematic comparison of consensus algorithms, including Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Byzantine Fault Tolerance (BFT) variations, assessing their impact on transaction speed, energy efficiency, and security. Additionally, the study examines Layer 1 (L1) and Layer 2 (L2) scaling solutions such as sharding, rollups, and sidechains to address blockchain's scalability challenges. The research also highlights emerging trends in blockchain development, particularly hybrid models and AI-driven optimization techniques, which can enhance blockchain efficiency and security. Results. The analysis reveals that different blockchain architectures exhibit varying trade-offs between decentralization, security, and scalability. Public blockchains, such as Bitcoin and Ethereum, prioritize decentralization and security but suffer from limited scalability. Private blockchains, in contrast, offer higher transaction throughput but compromise decentralization. Hybrid blockchains aim to balance these aspects by integrating the strengths of both models. A detailed comparison of consensus mechanisms indicates that PoW, while highly secure, is energy-intensive and slow, whereas PoS and its variations provide faster and more energy-efficient alternatives. The study also finds that Byzantine Fault Tolerance-based mechanisms, such as PBFT and DBFT, offer high-speed consensus suitable for enterprise applications. Furthermore, Layer 1 improvements, including sharding, enhance on-chain transaction processing, while Layer 2 solutions, such as optimistic rollups and zero-knowledge rollups, significantly increase throughput by offloading computations to secondary layers. The research highlights recent advancements, such as AI-assisted transaction validation and adaptive consensus algorithms, as promising directions for blockchain scalability and security. Conclusions. The study underscores the importance of optimizing blockchain scalability and consensus mechanisms to enable broader adoption across industries. While Layer 1 and Layer 2 solutions provide significant improvements in throughput and efficiency, their integration remains a key challenge. The findings suggest that hybrid consensus models and AI-based optimizations could further enhance blockchain performance, reducing energy consumption while maintaining security and decentralization. Future research should focus on developing dynamic sharding techniques, parallel consensus mechanisms, and predictive analytics for transaction management to advance blockchain's applicability in large-scale real-world scenarios. The continued evolution of blockchain technology will play a critical role in shaping secure, efficient, and decentralized digital ecosystems. Keywords: blockchain, decentralization, consensus mechanisms, optimistic rollups, sharding, transaction validation.
This article explores the potential of integrating blockchain technologies into public management of Ukraine's agricultural sector for post-war recovery through the lens of ESG principles. The authors analyze limitations of traditional regulatory models, particularly information asymmetry, lack of transparency in state support distribution, and limited access to financing for small and medium agricultural producers. The proposed concept envisions transforming state institutions from monopolistic regulators into infrastructural participants of network partnerships. The research reveals significant shortcomings in existing financing mechanisms, where approximately 75% of small agricultural enterprises face loan rejections, while traditional international payment instruments are characterized by high costs and low efficiency. The authors propose implementing agricultural asset tokenization mechanisms based on distributed ledger technology, enabling transparent, automated, and inclusive mechanisms for state support and private financing. A comparative analysis of traditional and innovative blockchain-based public management models is developed according to criteria of transparency, trust-building mechanisms, operational efficiency, and adaptability to ESG requirements. The study examines mechanisms for tokenizing agricultural assets with integrated ESG parameters, ensuring programmable responsibility of producers for compliance with environmental, social, and governance standards. Methods for implementing ESG standards are presented through: tokenization of ESG obligations, decentralized ESG certification, and programmed ESG regulation. Practical implementation of the proposed instruments is illustrated using examples of a decentralized blockchain platform for pre-ordering food poppy products and carp farming. The authors demonstrate that integrating distributed ledger technology creates conditions for democratizing market access, supply chain transparency, and automated verification of ESG criteria compliance, transforming them from regulatory requirements into competitive advantages. Implementing the proposed model requires not only technological modernization but also institutional transformation of regulatory bodies and development of specialized digital inclusion programs to bridge the digital divide in rural areas.
This article substantiates a new paradigm for managing state target programs based on distributed logic implemented through blockchain technologies and artificial intelligence (AI). The theoretical section analyzes the limitations of the centralized model for implementing state target programs, particularly high transaction costs, corruption risks, and management inefficiencies inherent in hierarchical systems. The research demonstrates that a distributed approach based on blockchain ensures data immutability and implementation transparency (through smart contracts and decentralized autonomous organizations), while AI application enables predictive analytics and dynamic resource planning, enhancing program adaptability. The authors propose a conceptual model of a «Distributed Target-Program» (DTP), which combines decentralized autonomous organizations (DAOs) for program management, smart contracts with KPIs for automatic performance control, a network of AI agents for monitoring and forecasting, and funding mechanisms through digital funds The methodological section provides a systematic analysis of experiences implementing distributed logic elements in Ukraine and worldwide. Examples examined include Estonia’s blockchain-based integrity of state registries, UN/World Food Programme (WFP) projects using blockchain for humanitarian assistance, digitalization of public services in Ukraine (the «Diia» mobile application), and blockchain solution experiments in the public sector. The research includes comparative case analyses of Ukrainian examples, such as blockchain implementation in social assistance provision (WFP Building Blocks project in Ukraine), the scale of digital aid payments through «Diia» (eSupport program), and DAO technology application in public administration. Special attention is given to assessing the regulatory compliance of the proposed solutions. The analysis covers current Ukrainian legislation in digital governance and public finance, as well as AI regulatory requirements according to the EU AI Act 2024/1689. The research demonstrates that implementing the DTP model requires legal framework adaptation (particularly defining DAO status and ensuring transparency and oversight of AI algorithms). This work is valuable for researchers and practitioners in public administration as it combines an interdisciplinary approach (public administration, information technology, legal aspects) and offers an innovative vision for the digital transformation of state programs.
With the widespread application of Cyber-Physical Systems (CPS) in intelligent manufacturing, ensuring the security and trustworthiness of components within the system has become a significant challenge. Traditional security control mechanisms face issues with managing large-scale device access, particularly in intelligent manufacturing production lines, where effectively managing the sharing and access permissions of security components is crucial. This paper proposes a smart contract-based secure component-sharing mechanism for intelligent manufacturing production lines, aiming to enhance the trustworthiness and efficiency of security component sharing within CPS. By combining blockchain technology with an Attribute-Based Access Control (ABAC) model, we design an SC-ABAC framework, which uses smart contracts to manage user attributes, component attributes, and access control policies, thereby ensuring trustworthy access control of security components. Within this framework, access requests go through a policy-matching process and attribute retrieval for users and components, with predefined rules determining whether access permissions are granted. The framework supports dynamic policy updates and deletions, providing more flexible security management. Furthermore, the dynamic access control function in the smart contract incorporates time-based conditions to enhance the precision of access control. By leveraging the decentralized nature of blockchain, this mechanism not only enhances data security but also reduces the fragmentation issues inherent in traditional access control systems. Experimental results verify the feasibility and effectiveness of the proposed framework.
This article discusses the current topic of the use of blockchain technologies in the digital economy. The study is based on an analysis of existing research and publications, as well as on the consideration of examples of the use of blockchain in various business areas. The main purpose of the work is to identify the challenges and prospects of using blockchain, as well as to assess its impact on economic processes. The advantages and disadvantages of using blockchain are discussed in detail, as well as recommendations for its effective implementation. In conclusion, the conclusions about the potential of blockchain technologies for the transformation of the digital economy and identifies possible areas for further research.
Mailson Teles-Borges, Rafael Z. Frantz, José Bocanegra, Sandro Sawicki · 5 authors
Smart cities take advantage of digital services to enhance citizens’ experiences. Integration processes facilitate interactions between these services, providing or improving functionalities. The integration can operate under specific restrictions, which can be represented through smart contracts deployed in a blockchain. Monitoring systems track interactions between integration processes and digital services by recording events from communication ports. In this paper, we argue that current monitoring tools lack the ability to observe these ports or invoke smart contracts. We propose a monitoring system to track integration processes, capture port-reported events, and invoke smart contracts on a blockchain platform.
Anniina Saari, Sarah Sinclair, Rebecca Leshinsky, Seppo Junnila
Digital transformation (DT) is complex and uncertain, particularly within traditional industries. Distributed ledger technology, such as blockchain, has driven DT across many global sectors. Despite its transformative potential, scaling blockchain solutions beyond pilot projects often fails due to technical, organisational and environmental barriers. Many failures stem from ineffective collaboration and strategic misalignment among ecosystem partners rather than from technology. This study examines collaborative processes and enabling capabilities required for successful DT by focusing on a longitudinal case study from Finland (2019–2023). The case follows a cross-industry, blockchain-driven DT initiative that achieved scale despite transitioning from private blockchain to centralised technologies after market entry. While blockchain's role in this success has been documented ( Saari et al., 2024 ), the ecosystem's collaboration mechanisms and strategies for tackling challenges remain unclear. Using the technology–organisation–environment (TOE) framework, this paper analyses how DT unfolded across these contexts, identifying best practice strategies and enabling capabilities. The study draws on 35 interviews with key stakeholders and thematic content analysis to identify critical scaling enablers. Our findings reveal that scaling blockchain-driven DT in cross-industry settings requires 1) industry-level mindset and shared vision, 2) formalised collaboration and public–private partnerships, 3) governance structure with a sustainable business model and funding, 4) complementary ecosystem roles and an early-stage champion, 5) stakeholder training and support and 6) flexibility in technology and agile implementation. These elements show that trust and strategic alignment can emerge even among direct competitors, offering valuable insights for enterprises exploring blockchain innovation in business-to-business contexts.
The integration of information technologies into all spheres of human activity, the proliferation of online communities, and the expansion of the virtual world have precipitated a transformation in consumer needs and an influence on their preferences. This paradigm shift has established the foundations for the emergence and development of digital assets, one notable example being the non-fungible token (NFT). The present article aims to examine the prospects for the development of non-fungible tokens (NFTs) in the context of global transformations in the digital asset market. A graphical method was employed in the study to identify global trends in the development of the NFT market. The use of a systematic approach allowed the identification of differences between NFT 1.0 and NFT 2.0. A comparative analysis was conducted to identify the strengths and weaknesses of the functioning of NFTs, as well as the threats and opportunities for the future existence of NFTs. A descriptive literature review allowed the development of optimistic, neutral and pessimistic scenarios for the development of the non-fungible token market. Product, functional and technological approaches to understanding non-fungible tokens were identified. The article examines NFTs in two forms: as digital assets and as digital certificates. The traditional and non-traditional reasons for using NFTs have been clarified. A comparative characterisation of NFT 1.0 and NFT 2.0 was made based on characteristics, ownership, participants, personalisation and areas of use. The article presents an analysis of the NFT market with a focus on its structural changes. The current state of the non-fungible token market is characterised by a shift from speculation to increased utility of NFTs in various sectors. The strengths and weaknesses of the functioning of non-fungible tokens were identified, as well as the threats and opportunities for their development in the context of global transformations. The study allowed the formulation of scenarios for the development of non-fungible tokens in the midst of critical transformations in the digital asset market. Under the optimistic scenario, market capitalisation, trading volumes, the number of users, the share of non-traditional NFT segments, the use of artificial intelligence in the creation of NFTs, the technical modernisation of NFTs and the legal regulation of all related relationships will increase. The neutral scenario will be characterised by volatility in market capitalisation, trading volumes and the number of market participants. In this scenario, regulation will focus on combating fraud and terrorist financing in the NFT market. In a pessimistic scenario, all key market indicators will decline, resulting in losses from non-fungible token transactions. In some jurisdictions, certain types of NFT transactions will be banned. The conclusions emphasise that with the expansion of the virtual world, NFTs are acquiring the characteristics of a digital product with high potential for use in various fields. The development of the NFT market is characterised by a combination of conflicting trends. On the one hand, there has been an increase in NFT capitalisation in early 2025, along with the growth of holders, buyers, and sellers in 2024. Conversely, there has been a decline in NFT trading volumes. These trends may provide the basis for the implementation of an optimistic scenario for the future development of the non-fungible token market.
Umar Al Faruq, Dwi Fitrizal Salim, Farida Titik Kristanti
This study conducted a large-scale analysis to evaluate the performance of traditional and Markov-Switching GARCH (MS-GARCH) models to estimate the volatility of the top 10 cryptocurrencies by market capitalization. The study compared the performance of the models using goodness-of-fit measures, specifically the Deviance Information Criterion (DIC) and the Bayesian Predictive Information Criterion (BPC). Secondly, we assess the forecasting accuracy for one-day-ahead conditional volatility and Value-at-Risk (VaR). The results obtained show that, in a manner consistent with the findings for the broader cryptocurrency market, the time-varying regime-switching model exhibits superior performance in capturing the complex volatility patterns observed in cryptocurrencies when compared to the traditional GARCH model.
To address the challenges of inefficiency, vulnerability to attacks, and the lack of transparency and fairness in distributed power trading, a distributed power trading mechanism based on blockchain smart contracts is proposed. Firstly, a strategy for matching distributed power trading orders is designed, and a model for managing user credit is constructed using the entropy weight method and deviation cost. Secondly, a smart contract for distributed power trading is compiled using the Solidity language. Finally, the designed smart contract is deployed, tested, and a distributed power trading network is simulated. The security analysis indicates that the Merkle Tree structure and PoW consensus mechanism effectively ensure the data and system security of distributed power transactions. Simulation test results demonstrate that the transaction mechanism can reliably complete transaction settlements, safeguard the interests of trustworthy users, and enhance the economic benefits of both parties involved in the transaction.
Anton Krivonogov, K. Starodubov, Alexander Prokofyev, Yuri Gromov
The article is devoted to the issue of sustainability of blockchain systems and their impact on the functioning of smart contracts that automate complex processes. An approach to determining the initial stability of a blockchain system is proposed, which includes the assessment of operational and technical parameters of the blockchain system using the method of direct expert evaluation. The proposed approach is tested on the example of the blockchain Ethereum.
Open access
Economic and Technological Systems Analysis
Digitalization and Economic Development in Agriculture
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