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.
Open access
2 source records
Opinion Dynamics and Social Influence
Advanced Research in Systems and Signal Processing
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.
Open access
Advanced Research in Systems and Signal Processing
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.
Open access
Cybersecurity and Information Systems
Advanced Research in Systems and Signal Processing
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.
Open access
Advanced Research in Systems and Signal Processing
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.
Open access
Blockchain Technology Applications and Security
Game Theory and Applications
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
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.
Open access
Cybersecurity and Information Systems
Advanced Signal Processing Techniques
Advanced Research in Systems and Signal Processing
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
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.
Open access
Advanced Research in Systems and Signal Processing
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 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
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.
Open access
Blockchain Technology Applications and Security
Advanced Research in Systems and Signal Processing
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
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
As digital technologies increase interconnectivity among us, the need to safeguard our network infrastructure from sophisticated cyber threats has never been more important. This chapter provides a review of the modern cybersecurity technologies that seek to protect our networks. A discussion of strategic approaches for protecting networks, tools needed, and the future of technology in cyber- protection. It has considered traditional forms of cybersecurity protection (e.g., firewalls, intrusion detection systems; IDS) along with modern AI-driven cyber threat detection and response. We discuss predecessor and subsequent paradigms of cybersecurity protection, including, but not limited to, zero trust architecture, the continued monitoring of networks as an operational method, and distributed ledger technology using blockchain; blockchain solutions like smart contracts and protocols (e.g., Hyperledger). Examining the trends in the future of cybersecurity protections, and highlight some of those that include predictive analytics and automated remediation of malware threats via Automated Threat Remediation, threat intelligence sharing, and a collaborative approach to countering threats. In summary, this chapter reinforced the importance of a low-latency, adaptive, and multi-layered defense approach to evolved cyber threats, and highlighted the need for organizations to demonstrate compliance with global standards and regulatory frameworks.
Open access
Network Security and Intrusion Detection
Advanced Research in Systems and Signal Processing
Blockchain-based tokenization is transforming the real estate sector, presenting a compelling alternative to the traditional model of Real Estate Investment Trusts (REITs). As the industry shifts from financialization to decentralization, driven by technological advancements, these two models offer different approaches to democratizing real estate investment.REITs have been a foundational aspect of real estate financialization, enabling individual investors to participate in large-scale real estate ventures through fractional ownership of diversified property portfolios. This has broadened the investor base and improved market liquidity. However, the emergence of blockchain technology and decentralized finance (DeFi) introduces a new paradigm: real estate ownership can now be fractionalized into digital tokens. This enhances liquidity, transparency, and accessibility through global 24/7 trading platforms. While REITs have made significant strides in expanding access to real estate investment, blockchain-based tokenization can further enhance these achievements by lowering entry barriers, reducing transaction costs, and decentralizing market operations. Nevertheless, the adoption of blockchain technology in real estate also comes with challenges, including regulatory uncertainties, technological risks, and the need for robust governance frameworks. As the lines between finance and technology continue to blur, it is essential to adapt regulatory frameworks and investment strategies to navigate this evolving landscape. The critical review highlights the future implications of these trends, emphasizing the importance of continued research and regulatory innovation to fully realize the potential of decentralized real estate markets. This is particularly relevant in addressing issues of housing inequality and affordability, as housing serves not only as an investment vehicle but also as a fundamental shelter for people.
Open access
2 source records
Advanced Research in Systems and Signal Processing
With the development of digital technologies, smart contracts are becoming an important tool for improving social networks. The research examines the integration of smart contracts for intelligent data analysis and process automation. These self-executing blockchain-based applications could revolutionize the way data management, content monetization, and user engagement are approached. The developed system provides automation of transactions, payments to authors, protection of personal data and decision-making in communities. This makes it possible to monitor user interaction in real time and analyze their activity, automatically recording and processing data without the intervention of intermediaries. This approach provides high transparency and accuracy, which makes it effective for researching social trends, identifying public opinion leaders, and evaluating content impact. Smart contracts also help streamline processes that previously required human intervention, keeping all actions and transactions stored on the blockchain transparent. This increases user trust and creates a fairer environment for interaction on the platform. Therefore, the developed system includes several technological aspects, such as blockchain, smart contracts, intelligent data analysis, as well as the integration of these technologies in social networks
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
This work is devoted to the research of the blockchain network, in particular, aimed at detecting illegal activity in the Ethereum network using forensic methods. The paper describes the concepts and basic vulnerabilities related to the Ethereum network and the integration of graph analysis to develop an algorithm that scrutinizes Ethereum's transaction structure for illegal activities, including money laundering. In addition, the study includes an analysis of the very structure of Ethereum and the blockchain, which allows insight into the identification and analysis of various aspects of their functioning. The research results are used for the software implementation of the study and improvement of the security level of the blockchain network, including the creation of advanced software solutions for network analysis and protection of the integrity of the blockchain ecosystem. This integrated methodology aims to protect the integrity of blockchain ecosystems.
Open access
Economic and Technological Systems Analysis
Advanced Research in Systems and Signal Processing
Blockchains have sparked global interest in recent years, gaining importance as they increasingly influence technology and finance.This thesis investigates the robustness of blockchain protocols, specifically focusing on Ethereum Proof-of-Stake. We define robustness in terms of two critical properties: Safety, which ensures that the blockchain will not have permanent conflicting blocks, and Liveness, which guarantees the continuous addition of new reliable blocks.Our research addresses the gap between traditional distributed systems approaches, which classify agents as honest or Byzantine (i.e., malicious or faulty), and game-theoretic models that consider rational agents driven by incentives. We explore how incentives impact the robustness with both approaches.The thesis comprises three distinct analyses. First, we formalize the Ethereum PoS protocol, defining its properties and examining potential vulnerabilities through a distributed systems perspective. We identify that certain attacks can undermine the system's robustness. Second, we analyze the inactivity leak mechanism, a critical feature of Ethereum PoS, highlighting its role in maintaining system liveness during network disruptions but at the cost of safety. Finally, we employ game-theoretic models to study the strategies of rational validators within Ethereum PoS, identifying conditions under which these agents might deviate from the prescribed protocol to maximize their rewards.Our findings contribute to a deeper understanding of the importance of incentive mechanisms for blockchain robustness and provide insights into designing more resilient blockchain protocols.
Open access
Economic and Technological Systems Analysis
Economic and Technological Developments in Russia
Advanced Research in Systems and Signal Processing
Lyudmila Kovalchuk, Nataliia Kuchynska, Mikhail S. Kondratenko
The paper investigates the issues of the safe operation of a two-level blockchain with a complex mixed consensus protocol — Proof-of-Stake in the main blockchain (mainchain) and Proof-of-Work in the secondary (sidechain). This two-level blockchain is built on the principle of the Proof-of-Proof protocol, where the safety of the sidechain is ensured by the stability of the mainchain, by referring the mainchain blocks to the sidechain blocks using special transactions. Such a structure allows faster issuance of blocks in the sidechain and, accordingly, faster processing of transactions without loss of security and without increasing the volume of the block. In turn, such a two-level blockchain is of the greatest interest for the creation of a cascade system of state registers, which will be guaranteed to be protected against the substitution and forgery of documents. The main results of the work are explicit analytical expressions for estimates of probability of double spend attack on such two-level blockchain, under the condition of adversary in sidechain and in mainchain. Keywords: blockchain, mainchain, sidechain, cryptocurrencies, mining, Proof-of-Proof consensus protocol, double spend attack.
Open access
2 source records
Blockchain Technology Applications and Security
Advanced Research in Systems and Signal Processing
Настоящая статья посвящена исследованию методов верификации данных в умных городах с использованием синергии искусственного интеллекта, распределённых реестров и сетевой теории. Актуальность вопроса определяется возрастающей сложностью городской инфраструктуры и необходимостью обеспечения безопасности, прозрачности и достоверности информации, поступающей с множества сенсоров и устройств в рамках концепции умного города. Во введении обоснована необходимость разработки новых методов проверки данных для повышения устойчивости и эффективности городских систем управления. Отмечается, что традиционные решения зачастую не справляются с масштабами и динамикой современного городского пространства, где данные генерируются в реальном времени и требуют быстрого анализа и подтверждения подлинности. В разделе «Методы» описаны использованные подходы, включающие алгоритмы машинного обучения для обработки и анализа информации, протоколы распределённых реестров, обеспечивающие неизменность данных, а также методы сетевого анализа, позволяющие выявлять ключевые узлы и связи в городской инфраструктуре. Проведён сравнительный анализ характеристик предложенных методов и технологий, что позволило сформировать единую методологическую модель верификации. Раздел «Результаты» демонстрирует, как применение интегрированной модели обеспечивает повышение надежности систем умного города. На основе экспериментальных данных показано, что использование комбинированного подхода позволяет существенно сократить число фальсификаций информации, а также оптимизировать процессы распределённой обработки данных. Выявлены основные закономерности и преимущества, связанные с синергией технологий искусственного интеллекта, блокчейн-решений и сетевой теории. В обсуждении делается акцент на перспективности интегрированных решений для устойчивого развития городской среды, а также рассматриваются вызовы и возможные направления дальнейших исследований. Авторы предлагают рекомендации по внедрению разработанных методов в реальные городские системы, что позволит обеспечить более гибкую, надёжную и саморегулируемую инфраструктуру умного города. Работа может стать основой для разработки новых стандартов верификации данных и улучшения взаимодействия между информационными компонентами городской среды. This article is devoted to the study of data verification methods in smart cities using the synergy of artificial intelligence, distributed registries and network theory. The urgency of the issue is determined by the increasing complexity of urban infrastructure and the need to ensure the security, transparency and reliability of information coming from multiple sensors and devices within the framework of the smart city concept. The «Introduction» substantiates the need to develop new methods of data verification to improve the sustainability and effectiveness of urban management systems. It is noted that traditional solutions often cannot cope with the scale and dynamics of modern urban space, where data is generated in real time and requires rapid analysis and authentication. The «Methods» section describes the approaches used, including machine learning algorithms for information processing and analysis, distributed ledger protocols that ensure data immutability, as well as network analysis methods that identify key nodes and connections in urban infrastructure. A comparative analysis of the characteristics of the proposed methods and technologies was carried out, which made it possible to form a unified methodological verification model. The «Results» section demonstrates how the use of the integrated model improves the reliability of smart city systems. Based on experimental data, it is shown that using a combined approach can significantly reduce the number of information falsifications, as well as optimize distributed data processing processes. The main patterns and advantages associated with the synergy of artificial intelligence technologies, blockchain solutions and network theory have been identified. The discussion focuses on the prospects of integrated solutions for the sustainable development of the urban environment, as well as discusses challenges and possible areas for further research. The authors offer recommendations on how to implement the developed methods into real urban systems, which will ensure a more flexible, reliable and self-regulating smart city infrastructure. This work can become the basis for developing new standards for data verification and improving interaction between information components of the urban environment.
Open access
Smart Cities and Technologies
Advanced Research in Systems and Signal Processing
The problem of monitoring a computer network under conditions of limitations on the use of system resources and high requirements for the survivability of the monitoring system has been considered. An autonomous decentralized computer network monitoring system has been developed, consisting of a team of software agents. Each agent can operate in two modes: main mode and monitoring system management console mode. In the main mode, the agent collects information about the computer network. In management console mode, the agent provides the user with access to information collected by all agents and allows the user to execute commands to manage the monitoring system. The developed monitoring system allows you to obtain more reliable information about the operation of the network with greater efficiency under the conditions of limitations on the use of system resources specified by the user. The autonomous monitoring system is created on the basis of the concept of multi-agent systems, within which a software agent of the system has some initiative for planning and implementing monitoring scenarios. The operation of software agents implements methods for organizing adaptive processes for collecting information using the principles of self-organization and the concept of structural adaptation. A decentralized software architecture for an autonomous monitoring system without a control center has been proposed. This ensures high reliability and survivability of the monitoring system. The software architecture of the autonomous monitoring system implements the SMA application software interface and the corresponding software library, which allows you to collect statistical data on the operation of the computer network and its nodes. The implementation of a software agent and a management console for an autonomous computer network monitoring system has been considered. Key words: computer network monitoring, autonomous system, decentralized control, software agent
Open access
Cybersecurity and Information Systems
Advanced Data Processing Techniques
Advanced Research in Systems and Signal Processing