Blockchain Papers

Adam David Kain

Sovereign entities – states, international organizations, and autonomous infrastructure networks – face a governance paradox: centralized systems become brittle under stress, while decentralized systems fragment into incoherence. This paper proposes the Constitutional Lattice v2.0, a mathematically structured frame-work for coordinating sovereign autonomy within a constitutional corridor, built on a three-term agent-interaction force law (oscillatory coupling, linear restoring, inverse-square repulsion) with a Lennard-Jones-style short-range hardening term. This paper is offered, in the spirit of a companion theoretical proposal in the psychotherapy and Human–AGI relational-dynamics literature [1], as a theoretical contribution with an explicitly preliminary empirical status. The framework’s central structural conjecture – that the coupling ratio ρ= kg /km has a privileged value at Φ−1 ≈ 0.618 – was tested computationally in a simplified two-dimensional setting (Section 6). The test did not find evidence supporting this conjecture: the measured stability metric varied smoothly and monotonically across the tested range of ρ, with no distinguishing feature at Φ−1. This result, its scope, and its limitations are reported in full, following the disclosure standard set out in [1]. The paper’s remaining contributions – the federated lattice architecture, the quarantine and cold-boot recovery mechanisms, and the Constitutional Drift Index as a transparency instrument – are presented as an architecture and a research programme, not as validated engineering.

V. V. Abramov

The article provides theoretical-game model of voting in decentralized autonomous organization, where honest participants and evil agents meaning harm to the system strategically interact. To restrain harmful behavior mechanism of reputation tokens, i.e. intangible assets accumulated for conforming voting and lost in case of inactivity or confronting decision. The access to voting is given only when the minimum reputation threshold is exceeded. The model shows the introduction of reputation can transform one-step dilemma of participation into dynamic game. The key result is identification of two principle types of balance: mixing one, when evil agents behave like honest for a certain period of time in order to accumulate influence for the future attack and separating one, when they reveal their type quickly and are expelled from the system. Analysis shows that mechanism effectiveness depends drastically on its parameters (amount of rewards and fines) and informational structure: complete information of agents about proposal value can raise effectiveness of goal-oriented attacks. On the basis of this analysis recommendations were provided for designing sustainable systems, including the necessity to combine reputation with other mechanisms (quorum, delegation) and adjust parameters with regard to the share of evil agents.

O. Kravets, B. Martynenkov, A. Tcvetkov, E. Puzhanova · 7 authors

The article discussed an algorithm for achieving mutual information coordination for a system with distributed ledger technology based on a blockchain. The goal is to develop a generalized approach to formalizing the operation of the distributed ledger technology blockchain system in the course of achieving mutual coordination, including taking into account the possibilities of implementing abnormal functions by the distributed ledger technology blockchain node of the system and grouping nodes. The rules of block chain formation in algorithms for achieving mutual information coordination are proposed. The process of achieving mutual information coordination is described. A mathematical model of the process of achieving mutual information coordination between the nodes of the distributed ledger technology blockchain system is proposed, which differs in the representation of the system by a team of finite automata with the possibility of creating associations (pools) and providing an assessment of the centralization of the system in the conditions of choosing different variants of behaviour strategy by automata.

V. V. Abramov, G. V. Kolesnik

One of the factors negatively affecting management effectiveness in decentralized autonomous organizations is implicit centralization of decision-making within a certain group of participants. Such centralization can be caused by both economic reasons related to uneven distribution of voting power and information and social ones related to participants’ status and control over information. The decision-making process in decentralized autonomous organizations has been analyzed in a situation when participants face information asymmetry, strategic behavior, and lack of centralized control. The principal–agent model has been considered as a formal basis, in which tokens’ holders act as the principal and project initiator, who forms an offer of a certain quality, as the agent. The conditions under which it is possible to form an equilibrium that ensures high-quality projects choice have been investigated. Incentive mechanisms have been proposed to ensure the interest in the principal’s participation in managing organization. Two directions have been considered: changing the agent’s remuneration structure based on payments differentiation and participation costs compensation for the principal. It has been demonstrated that minimal institutional changes can significantly improve organization’s management effectiveness, while maintaining decentralized nature of decision-making.

K.A. Putkov, Р.Ю. Овсянников

The research addresses the pressing issue of security, immutability, and data synchronization in interbank interaction systems. Traditional centralized architectures, such as SWIFT, demonstrate vulnerabilities, including risks of unauthorized access and high operational costs for reconciliation and data alignment between participants. The aim of the work is to design a protocol concept based on private Distributed Ledger Technology (DLT), which ensures the creation of a unified, cryptographically secured, and synchronized transaction ledger. The article justifies the choice of a private blockchain model with a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm for achieving agreement among trusted node-participants. Key elements of the protocol are smart contracts for automating settlement business logic and a multi-level cryptographic system with mandatory multi-signature. The result is an architectural model that eliminates the risks of data falsification, ensures end-to-end auditability of all operations, and significantly reduces the time and financial costs associated with post-transaction reconciliation. The issues of compliance of the proposed solution with current regulatory requirements in the financial sector are separately considered.

Emir Osmanspahić

No abstract is available for this record.

Daniel J. Moroz

A key scientific question underlying the blockchain ecosystem is to what extent the core security properties of the protocols hold when assuming rational validators in the presence of capable economic attackers. To what degree and at what cost can these systems be disrupted? In this thesis, I analyze the underlying economic security properties of three of the most fundamental decentralization consensus algorithms: proof of work (PoW), proof of stake (PoS), and oracle information aggregation. In Chapter 2 of this work, I counter a prominent narrative that PoW is inherently flawed in an environment in which double-spend attacks are possible. By considering counterattacks, I recover PoW robustness against reorganization attacks through a game-theoretic model. In particular, I consider hashrate markets as a potential vector of attack and show that PoW remains robust in this case. In Chapter 3 of this work, I show novel chain reorganization and finality-delay attacks on the PoS mechanism of Ethereum. These attacks are deviations from the ’honest’ staking strategy, and I show that for participants staking a substantial percentage of the network’s staked assets, these attacks can be cheap and destructive to the network. In Chapter 4 of this work, I design an incentive mechanism for the information aggregation of noisy signals that is highly resilient to bribery. I establish the asymptotic strength and limitations of this mechanism against various classes of bribery including an attacker able to condition bribes on individual reports and on the outcome of the information aggregation. I achieve strong protection even in the latter case. To do this, I assume the presence of a source of truth (SoT) that is prohibitively expensive for typical use but can be invoked infrequently. This robustness to bribes is achieved even while in equilibrium there is no invocation of the SoT.

А. М. Макаров, Е.А. Писаренко, Б. М. Гаджимурадов

В статье представлена обобщенная модель иерархической информационной системы с распределенным реестром на основе блокчейн-технологии для цифровой среды управления государством. Рассмотрена трехуровневая архитектура системы: федеральный, региональный и муниципальный уровни. Описан протокол включения новых блоков в одноранговую блокчейн-цепь с механизмом достижения консенсуса. Предложенная модель обеспечивает криптографически технологическое доверие между абонентами всех уровней системы при создании электронных государственных услуг и сервисов.

Iman E. Murdalova

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.

Borislav Borisov

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.

I. N. Rozenberg, Ia. M. Dalinger

Possibilities to use distributed ledger technology are shown referring to storing data in information systems of airports and aviation systems of various levels. The features of the operation of a distributed ledger are noted regarding information systems. Various options for generating messages for storage using distributed ledger technology are studied along with the parameters of message flows. The features of using blockchain technology when creating distributed ledger are highlighted in case of the need to correct the stored information. Apossibility to use network technologies is shown for forming distributed ledger, the nodes of which are located at significant distances from each other (registries of several airports). The provided data can be used to create reliable distributed information storage facilities, both within a separate airport and for a group of airports.

Vasiliy Krundyshev, Oleg Vasiliev, Maxim Kalinin, A. S. Konoplev

No abstract is available for this record.

M. O. Kalinin, V. M. Krundyshev, O. S. Vasil’ev

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.

Vladyslav Prosolov, Gennady Khalimov, Pavlo Shulik, Anton Smirnov · 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.

Yevhenii Demenko, Igor Grebennik, Maksym Kolmykov

The problem of reproducibility of experiments in optimizing validator allocation in blockchain networks with Proof of Stake consensus was investigated, in particular due to the absence of standardized datasets and unified testing methods, which complicates the objective comparison of algorithms. To tackle this issue, we propose a method for building test datasets that rely on deterministic pseudorandom sequence generators and validator profiles calibrated against Ethereum network statistics. Each validator is described by a set of parameters that includes the stake size with the minimum requirement according to Ethereum standards, performance with a uniform distribution, reliability in a high range, network delays depending on the geographical proximity of participants, geographical location according to the actual statistics of validator distribution by regions, quality of network connection, and slashing history according to the violation statistics in the Beacon Chain. Three datasets of different scales were created for small, medium, and large network configurations with fixed initial values of the generators to ensure full reproducibility of experiments. A multi-criteria evaluation system was developed based on a generalized quality indicator that maximizes system throughput and minimizes load imbalance and network delays with scientifically grounded weighting coefficients. The tenfold testing protocol ensures the statistical reliability of results and reduces the impact of randomness on conclusions. The experiments conducted a comparative analysis of four allocation algorithms: a hybrid metaheuristic method based on particle swarm optimization with local search, random allocation with correction, an adapted Ethereum shuffling mechanism, and a greedy algorithm. The experimental results revealed scale-dependent efficiency of the algorithms: the hybrid method provides high optimization quality at all investigated scales, but quadratic growth of execution time limits its application to periodic offline planning of network configuration; the shuffling mechanism demonstrates stable medium-quality results with fast execution; the random method is characterized by moderate speed with variable results; the greedy algorithm shows maximum speed with deterministic results but variable efficiency depending on the network scale. The proposed method forms a basis for standardizing experimental research in Proof of Stake consensus systems. It ensures the objective comparison of new algorithmic solutions for validator allocation in decentralized blockchain networks.

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.

А.В. ЩЕРБАКОВ

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.

Yevhenii Kovalchuk

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.

Нурлан Ташатов, Руслан Оспанов, Yerzhan Seitkulov, Дина Сатыбалдина · 5 authors

The rapid progress in artificial intelligence technologies in recent years has been largely driven by advances in reinforcement learning (RL). RL methods have proven to be highly effective in solving many practical problems. Distributed ledger technologies are finding wide application in the internet of things (IoTs), providing new approaches to solving problems of traditional IoT systems. Consensus is a fundamental component of distributed ledger technologies, responsible for ensuring data consistency between nodes, its security and accuracy. This paper is devoted to the study of the optimal choice of blockchain consensus protocol for IoT networks based on a combination of multi-criteria decision making (MCDM) and RL methods. The paper discusses the potential of merging MCDM and RL methods for selecting blockchain consensus protocols in IoT networks. It suggests a combined framework for effective protocol selection and management.

P. Meenalochini

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.

Ali Uzunkaya, Suat Topuz, Önder Halis Bettemir

No abstract is available for this record.

Nazym Kaziyeva, Руслан Оспанов, Dmitry Zernov, NC "Kazakhstan Garysh Sapary · 5 authors

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

А. О. Твердохліб

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.

Fathe Jeribi, Mohammed Shuaib, Shadab Alam, A. Rajaram

This study proposes a system for real-time structural health monitoring (SHM) including blockchain technology, deep learning, and piezoelectric transducers. Piezoelectric devices gather mechanical energy from external vibrations and also sense structural changes and transfer them into electrical impulses, acting both as transducers and sensors. principal component analysis (PCA) and root mean square deviation (RMSD) serve to expose structural anomalies in these data. Selected for its capacity to record both past and future temporal dependencies in sequential data and assess these characteristics to predict the health state of infrastructure components, a bidirectional long short-term memory (Bi-LSTM) model. The model exceeds traditional models in high prediction accuracy of up to 98.79% at low voltages with a mean absolute error (MAE) of 1.445, a recall of 100%, and an F1-score of 98.3%. Blockchain technology is used for unchangeable recording of anomaly forecasts and sensor data integrity and automation guarantee. Smart contracts instantly start to offer real-time alarms and distributed system governance from a distance when fault thresholds are exceeded. Especially suited for smart cities, bridges, other essential infrastructure, this design increases openness, reduces dependency on centralized systems. The results demonstrate that this combined approach for intelligent infrastructure monitoring is realistic for sustainable growth.