This article examines the architecture of a secure information system built on distributed ledger technology. It substantiates the need to transition from a centralized data storage model to a distributed trusted environment that ensures cryptographic verification of transactions, immutability of records, and resistance to compromise of individual nodes. A multi-tiered system architecture is proposed, including subsystems for identification, access control, event registration, cryptographic protection, and anomaly monitoring. Particular attention was paid to aligning the designed model with the requirements of the Federal Service for Technical and Export Control of Russia for threat modeling and the provisions of GOST R 34.10-2012 on electronic digital signatures. An integrated security indicator was developed to assess the integrity, availability, and confidentiality of data.
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
This report examines smart contracts as a key element in the development of decentralized systems and as a factor for a profound transformation of traditional contract law.The analysis focuses on the essence of smart contracts, their technological mechanism of action and the role of cryptography in ensuring trust and security without the need for a central intermediary.Particular attention is paid to the way in which program code begins to perform functions traditionally inherent in legal norms and institutions.Smart contracts are not just a technical tool, but a new socioeconomic mechanism for regulating relations between entities in a digital environment.The report also examines the concept of "Code is Law" as a philosophical and practical framework that questions the classical legal principles of interpretation, flexibility and judicial review.Both the potential benefits of this paradigm and the risks arising from full automation are analyzed.Additionally, the main vulnerabilities of smart contracts that arise as a result of human errors when writing the code and the irreversibility of actions in a blockchain environment are examined.These risks show that technological security does not always mean legal justice.Finally, the legal status of smart contracts in Bulgaria and the European Union is examined.
Open access
Cryptography and Data Security
Advanced Research in Systems and Signal Processing
Subject. This article discusses the issues related to the oversight of decentralized finance. Objectives. The article aims to search for the optimal conditions for the effective implementation of the embedded supervision of decentralized finance. Methods. For the study, I used retrospective, systems, and functional and structural analyses, classification, comparison, and generalization. Results. The article describes the main problems and ways to solve them in terms of economic analysis of the embedded supervision over decentralized finance. It defines the built-in analysis and optimal conditions for its implementation. The article proposes mathematically determined parameters and recommendations for implementing embedded supervision related to the behavior of nodes and consumption of their register for confirming operations with digital property. Conclusions. The proposed economic and mathematical approaches help formalize the task of embedded supervision in the DeFi environment, and find solutions that take into account the interests of all market participants, as well. The optimization models discussed demonstrate the possibility of balancing the need for transparency and the need to preserve the main benefits of decentralization.
Sustainable Finance and Green Bonds
Digitalization and Economic Development in Agriculture
The article proposes an algorithm for alerting the population in case of fires using feedback via SMS and mapping services. The mechanism integrates distributed ledger technology and artificial intelligence to improve the accuracy, coverage and adaptability of the system. The article also develops a model that takes into account the distribution of population density during alerting in a given zone, as well as the optimal radius of the alert zone. The model is implemented in the form of software “Model of the effective radius of alerting in case of fire”. Results. The results obtained can be used to adjust the existing model of public notification in case of large fires, both natural and man-made. This work is intended for those who make managerial decisions and manage the forces and means of extinguishing fires.
Abstract This article examines the problem of ensuring Byzantine fault tolerance in the distributed ledger systems of a smart city. To improve the security of distributed ledger systems, it is proposed to use the Hashgraph distributed consensus protocol, in which events are organized as a directed acyclic graph and nodes exchange “gossip about gossip.” The traditional Hashgraph protocol is supplemented with a developed trust model that reduces the influence of malicious devices when reaching consensus in the digital infrastructures of a smart city.
Advanced Research in Systems and Signal Processing
The article examines the theoretical foundations for selecting algorithms and data structures to ensure secure storage and processing of metadata in IoT systems using the Ethereum blockchain. A classification of metadata types specific to heterogeneous IoT environments is presented, taking into account semantic significance, update frequency, and data criticality. Formal requirements for algorithms are formulated, covering resistance to forgery, computational complexity, scalability under high-intensity request loads, and resource efficiency in terms of gas costs and network throughput. A comparative analysis of data structures employed in the Ethereum infrastructure, including Merkle Tree, Merkle-Patricia Trie (MPT), Multi-State MPT, and GPU-accelerated modifications, is performed according to criteria such as asymptotic complexity, memory efficiency, and suitability for incremental updates. A conceptual model for organizing metadata exchange between IoT nodes and smart contracts is proposed, incorporating modules for encoding, verification, gas cost optimization, and standardized interaction interfaces. The presented results provide a theoretical basis for developing formally verified and energy-efficient solutions in the field of secure Ethereum blockchain integration with the Internet of Things.
The study's relevance is determined by the critical dependence of cryptocurrency market stability on thetechnical reliability of smart contracts and the increasing risks of financial losses due to their defects. Aim:The aim of the study is to formalize the ranking of technical vulnerabilities of smart contracts by theirimpact on the economic stability of domestic capital markets through systematization, simulationmodelling, and quantitative assessment of financial indicators. Methods: The research used the followingtechniques: vulnerability typing, simulation modelling, financial analytics, and comparative analysis.Obtained results: The study confirmed the critical impact of smart contract technical vulnerabilities on thefinancial stability of the markets, with peak VaR of up to -68.5% and liquidity deterioration of over -80%for reentrancy attack, delegatecall injection, and oracle manipulation. The risks were reduced by more thanhalf after implementing multi-level optimisations, demonstrating the effectiveness of comprehensivemitigation to stabilise key financial indicators. Academic novelty of the study: The academic novelty of thestudy is the formalized classification of technical vulnerabilities of smart contracts and the first empiricalassessment of their impact on the economic stability of capital markets based on comprehensive financialand economic metrics, which extends the theory of DeFi structural risks. Prospects for future research:Prospects for further research include the development of a pilot project for technical optimization ofsmart contracts with a focus on increasing resilience to logical and synchronization defects.
Reliable asset price data are critical for the functioning of decentralized finance (DeFi) protocols, particularly those involving collateralized lending. The accuracy of blockchain-based price oracles directly affects key processes such as collateral valuation, liquidation, and risk management. This paper presents a comprehensive empirical analysis of Chainlink Price Feeds (CPFs), the dominant oracle infrastructure in DeFi. We compile a novel dataset of over 150 million observations from 40 CPFs on Ethereum over an 18-month period, matched to benchmark prices from a centralized exchange. To identify the determinants of oracle inaccuracy, we estimate pooled OLS and fixed effects regressions, relating price deviations to design parameters, reporter dynamics, and market conditions. We then introduce a Markov-like state transition framework to model the resolution of target corridor violations, using multinomial logistic regression to estimate transition probabilities. Finally, we exploit position-level data from one of the largest decentralized lending markets and apply entity fixed effects regressions to examine how users adjust collateralization in response to oracle design. Our findings highlight economically significant deviations that are systematically related to oracle accuracy configurations and market stress, and show that users internalize these risks in their financial decisions. The results offer new insights for the design of resilient oracle systems and the management of risk in decentralized financial markets.
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
This study is a comprehensive analysis of the prospects for the development of cryptocurrencies Bitcoin and Ethereum in the context of global economic and political transformations, revealing the fundamental ambivalence of their nature through the dialectic of nominal capitalization and the lack of a stable value paradigm. Using a synthetic methodology combining econometric volatility analysis with an institutional approach, the paper reveals a systemic correlation of the market dynamics of the assets under study with shadow financial flows and speculative practices, demonstrating their permanent dependence on behavioral patterns of mass demand rather than objective macroeconomic factors. Special attention is paid to the process of increasing marginalization of Bitcoin and Ethereum in the system of legitimate economic transactions against the background of the observed convergence of user preferences towards stablecoins, which, combined with extreme price fluctuations (up to +50%), which are stochastic, finally negates their investment viability. The results obtained make it possible to predict with a high degree of reliability the systemic risks of correction by 50% or more due to the fundamental vulnerability of these crypto assets as speculative instruments that do not have price stabilization mechanisms in conditions of geo-economic turbulence.
This paper explores the integration of Blockchain technology into Structural Health Monitoring (SHM) to enhance data traceability, integrity, and automation in infrastructure asset management. Traditional SHM approaches, including Digital Twin-based systems, often face limitations related to data tampering, sensor unreliability, and the lack of transparent and verifiable data workflows. To address these challenges, the SHERPA framework is proposed. SHERPA leverages decentralized storage via the InterPlanetary File System and three Smart Contracts dedicated to data validation, anomaly flagging, and automated workflow execution. Rather than focusing on the structural interpretation of data, SHERPA establishes a secure and auditable backbone for SHM data governance. A prototype implementation on the Canalone Viaduct in Italy demonstrated the feasibility of the system, showcasing automated response to threshold violations and immutable data registration. The framework proved effective in enhancing transparency, traceability, and stakeholder confidence, positioning SHERPA as a promising enabler of more trustworthy and accountable SHM systems.
Stanislav I. Trofimov, Leonid Voskov, Mikhail Komarov
In the face of growing competition in the transportation market, companies are looking for new ways to improve operational efficiency and reduce fleet maintenance costs. This article presents an innovative vehicle technical condition management model that describes a mechanism for assessing the condition of vehicles using distributed ledger technology (DLT) and smart contracts. An information system for automating maintenance is proposed that can perform monitoring functions and initiate vehicle maintenance without human intervention by automatically registering operation and maintenance events, as well as using smart contracts to launch predefined actions. This level of automation allows timely prevention of unplanned breakdowns, which directly contributes to an increase in the service life of vehicles. The proposed solution allows transport companies to automate decision-making processes on maintenance, reduce transport downtime and optimize operating costs. The model ensures transparency of vehicle operation data, increases trust in information and shortens the decision-making chain. The solution is of particular value for public transport companies, where uninterrupted transportation and passenger safety are critically important.
Open access
Transportation Systems and Logistics
Advanced Research in Systems and Signal Processing
The US Department of Transportation (USDOT) delivers a wide range of infrastructure projects, backed by a fiscal year 2023 budget exceeding $100 billion. These projects face mounting pressures to meet performance, accountability, and delivery standards, driven by their dependence on public funding and their operational complexity. Transportation infrastructure presents sector-specific challenges—such as time-sensitive user disruptions, multiparty coordination, and asset intersection risks—that demand more robust, automated, and transparent project delivery mechanisms. Blockchain-enabled smart contracts have emerged as a promising solution to address these operational pain points through real-time automation, immutable data records, and decentralized transaction processing. However, the practical realities of the transportation sector—its fragmented systems, regulatory layers, and diverse stakeholder interfaces—create unique integration challenges that remain underexamined. To address this, this study investigates how smart contracts can be effectively integrated into transportation infrastructure by identifying the context-specific needs, requirements, capabilities, and challenges that govern their adoption. A three-phase research design was employed. First, a literature review was conducted to extract generalized integration factors for smart contract use in the broader construction domain. Secondly, these factors were evaluated and ranked by qualified transportation experts to reflect their relevance in sector-specific contexts. Thirdly, structural equation modeling (SEM) was used to analyze expert survey responses and isolate the most influential integration drivers. The results indicate that, unlike general construction projects, the top integration priorities in transportation include (1) compliance checking for quality management (needs); (2) integration with existing cloud repositories or enterprise platforms (requirements); (3) the ability to maintain immutable records (capabilities); and (4) uncertainty regarding usability (challenges). These findings provide a targeted knowledge base for practitioners and policymakers, outlining the critical considerations required for effective and sector-sensitive implementation of smart contracts in transportation infrastructure.
Purpose. The aim of the study is to develop a detailed role model for the implementation of smart contracts in the logistics processes of freight transportation, which will enable the automation of interaction between participants and increase the transparency of operations. Methodology. To achieve the stated goal, a systemic approach using context-role analysis was applied. The study involves a detailed decomposition of the stages of the logistics chain when applying smart contracts, identification of key participants, and definition of their functions, rights, and responsibilities. This approach makes it possible to clearly delineate areas of responsibility, reduce the risk of conflicts, and ensure the transparency of each participant’s actions. The developed UML diagram demonstrates the sequence of interactions between subjects, and the integration of smart contracts ensures the automation and immutability of operations. Findings. A comprehensive analysis of logistics processes using smart contracts was carried out, which made it possible to define the rights and responsibilities for seven basic roles of logistics operation participants. This approach provides a holistic view of the system and makes it possible to describe the logic of interactions between subjects. The developed model demonstrates the automation of contract conclusion and execution, which contributes to the reduction of document processing time, optimization of operations, and ensuring a high level of data security in the distributed ledger. Originality. An approach is proposed that enables the integration of formalized roles of freight transportation participants with smart contract technology. The detailed structuring of the functional responsibilities of each role makes it possible to implement the program logic of a decentralized system, which significantly expands the possibilities of automated logistics process management. The approach is universal and can be adapted to different types of logistics scenarios. Practical value. The developed role model creates favorable conditions for the implementation of blockchain solutions in the field of freight transportation, which makes it possible to digitalize logistics processes, increase trust between supply chain participants, and reduce operational costs. The obtained results have practical application for logistics operators, software developers, and consulting companies that seek to modernize existing transportation management systems. The model can also be useful for educational purposes in the fields of logistics, computer science, and management.
Andrew Hudson‐Smith, Duncan Wilson, Valerio Signorelli
This chapter explores the complex interplay between economics and security in the rapidly evolving metaverse. It examines the economic dynamics underpinning virtual worlds, including the rise of cryptocurrencies, non-fungible tokens, and digital asset ownership. We examine case studies of economic systems within platforms like Second Life, Decentraland, and Fortnite, highlighting the substantial real-world value generated in these virtual economies. The chapter also addresses the critical security challenges facing the metaverse, including cybercrime, terrorism, and jurisdictional issues in enforcing laws across digital borders. It recounts one of the earliest documented virtual terrorist attacks and discusses the need for robust security measures to protect users and digital assets. We conclude by emphasising the frontier nature of the metaverse, its potential for economic growth and innovation, and the critical importance of balancing security concerns with the development of this new digital frontier.
В статье представлен комплексный анализ принципов функционирования и особенностей децентрализованных систем. Исследование направлено на изучение механизмов обеспечения устойчивости, безопасности и математического моделирования таких структур. Применены методы системного анализа, теории графов и агентного моделирования. Выявлены ключевые характеристики децентрализованных систем: отказоустойчивость, масштабируемость, автономность узлов. Установлено, что эффективность таких систем достигается через механизмы консенсуса, распределенного хранения данных и самоорганизации. Результаты исследования демонстрируют перспективность применения децентрализованных структур в различных сферах - от финансов до государственного управления. The article presents a comprehensive analysis of operational principles and characteristics of decentralized systems. The research focuses on studying mechanisms for ensuring resilience, security, and mathematical modeling of such structures. Methods of system analysis, graph theory, and agent-based modeling are applied. Key characteristics of decentralized systems are identified: fault tolerance, scalability, and node autonomy. It is established that the efficiency of such systems is achieved through consensus mechanisms, distributed data storage, and self-organization. The research results demonstrate the promising potential of applying decentralized structures in various fields from finance to public administration.
Advanced Research in Systems and Signal Processing
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.
The construction supply chain often faces challenges such as contract disputes, inefficient payments, and difficult claim management due to its complexity and the involvement of multiple parties. Most existing solutions focus on optimizing contract terms or improving local processes, but they lack systemization, automation, and transparency. Therefore, this study proposes a claim and payment process management model based on blockchain and smart contracts, aiming to achieve digital and automated governance of the construction supply chain. The study constructs three types of smart contracts: The supply chain decomposition smart contract automatically divides engineering projects into independent billing cycles. The billing unit smart contract monitors the compliance of construction. The negotiation and settlement smart contract automatically handles disputes and payments. These three types of smart contracts work together to form a decentralized dynamic management framework. Through simulation experiments comparing the traditional process with the smart contract model, the results show that in scenarios with a high probability of claims and a large proportion of construction defects, the capital flow efficiency of the smart contract model is increased by more than 20%, and it shows stronger stability under high claim risks. The contribution of this study lies in combining blockchain technology with the logic of supply chain decomposition, proposing a smart contract system applicable to dynamic engineering projects, thus providing a digital processing method for the integrated management of claims and payments in the construction supply chain. This digital dynamic management method can ultimately systematically solve the island problem in supply chain claim research. Its automated and transparent characteristics help reduce dispute costs and enhance trust among multiple parties, which has important practical significance for improving the overall efficiency of the industry.