This article is an ethnographic account of the State Machine One (SMO) gigalopolis. It offers the first modern mapping of the social imaginaries found within the network states, coordi-nations and agoras of State Machine One (SMO). It further provides insight into the operations of SMO’s Ethereum Ecosystem C (EEC) polycentric governance system. The author was invited to engage in this research by the University of Dencun and received academic immunity to travel across the major sectors of SMO. Employing New Grounded Theory, it presents State Machine One as a complex, heterogenous, but broadly cohesive political entity at its core. The author finds strong evidence of Ethereum Alignment across SMO, but also the presence of an ungovernable region known as Free Ross and some unusual reports from beyond the Exclusion Border.
Tracking the evolution of smart contracts is challenging due to their immutable nature and complex upgrade mechanisms. We introduce EvoChain, a comprehensive framework and dataset designed to track and visualize smart contract evolution. Building upon data from our previous empirical study, EvoChain models contract relationships using a Neo4j graph database and provides an interactive web interface for exploration. The framework consists of a data layer, an API layer, and a user interface layer. EvoChain allows stakeholders to analyze contract histories, upgrade paths, and associated vulnerabilities by leveraging these components. Our dataset encompasses approximately 1.3 million upgradeable proxies and nearly 15,000 historical versions, enhancing transparency and trust in blockchain ecosystems by providing an accessible platform for understanding smart contract evolution.
Chun-Wing Poon, James T. Kwok, Calvin Chow, Jieun Choi
Anti-money laundering (AML) systems are important for protecting the global economy. However, conventional rule-based methods rely on domain knowledge, leading to suboptimal accuracy and a lack of scalability. Graph neural networks (GNNs) for digraphs (directed graphs) can be applied to transaction graphs and capture suspicious transactions or accounts. However, most spectral GNNs do not naturally support multi-dimensional edge features, lack interpretability due to edge modifications, and have limited scalability owing to their spectral nature. Conversely, most spatial methods may not capture the money flow well. Therefore, in this work, we propose LineMVGNN (Line-Graph-Assisted Multi-View Graph Neural Network), a novel spatial method that considers payment and receipt transactions. Specifically, the LineMVGNN model extends a lightweight MVGNN module, which performs two-way message passing between nodes in a transaction graph. Additionally, LineMVGNN incorporates a line graph view of the original transaction graph to enhance the propagation of transaction information. We conduct experiments on two real-world account-based transaction datasets: the Ethereum phishing transaction network dataset and a financial payment transaction dataset from one of our industry partners. The results show that our proposed method outperforms state-of-the-art methods, reflecting the effectiveness of money laundering detection with line-graph-assisted multi-view graph learning. We also discuss scalability, adversarial robustness, and regulatory considerations of our proposed method.
Ilham Qasse, Isra M. Ali, Nafisa Ahmed, Mohammad Hamdaqa · 5 authors
The immutability of smart contracts on blockchain platforms like Ethereum promotes security and trustworthiness but presents challenges for updates, bug fixes, or adding new features post-deployment. These limitations can lead to vulnerabilities and outdated functionality, impeding the evolution and maintenance of decentralized applications. Despite various upgrade mechanisms proposed in academic research and industry, a comprehensive analysis of their trade-offs and practical implications is lacking. This study aims to systematically identify, classify, and evaluate existing smart contract upgrade mechanisms, bridging the gap between theoretical concepts and practical implementations. It introduces standardized terminology and evaluates the trade-offs of different approaches using software quality attributes. We conducted a Multivocal Literature Review (MLR) to analyze upgrade mechanisms from both academic research and industry practice. We first establish a unified definition of smart contract upgradeability and identify core components essential for understanding the upgrade process. Based on this definition, we classify existing methods into full upgrade and partial upgrade approaches, introducing standardized terminology to harmonize the diverse terms used in the literature. We then characterize each approach and assess its benefits and limitations using software quality attributes such as complexity, flexibility, security, and usability. The analysis highlights significant trade-offs among upgrade mechanisms, providing valuable insights into the benefits and limitations of each approach. These findings guide developers and researchers in selecting mechanisms tailored to specific project requirements.
The rapid advancement and adoption of blockchain technology have fundamentally transformed various aspects of digital interaction, leading to the emergence of novel governance frameworks that challenge traditional centralized models. At the forefront of this transformation are decentralized autonomous organizations (DAOs) and an array of other governance structures applied in both permissionless and permissioned blockchain environments. Unlike conventional organizations that rely on hierarchical authority, DAOs within permissionless systems strive to operate through decentralized networks where decision-making power is distributed among all members, facilitated by smart contracts and governance tokens. In parallel, permissioned blockchain applications, often employed by consortia or enterprises, experiment with more structured membership and delegated authority, blending decentralized principles with selective participation to maintain compliance, accountability, and operational efficiency. These governance mechanisms, whether in DAOs or permissioned networks, are envisioned to enhance transparency, inclusivity, and autonomy. Yet, despite their idealistic promises, practical implementations have revealed significant challenges. Within DAOs, governance tokens intended to promote equitable decision-making often lead to power concentration and stakeholder inequality. Moreover, vulnerabilities in smart contract design and the absence of robust accountability frameworks have produced notable failures. In permissioned contexts, while governance structures can mitigate some of these issues through established roles and clearer recourse mechanisms, complexities arise in balancing decentralized ideals with enterprise-grade stability and oversight. This thesis critically examines the foundational principles of blockchain-based governance—spanning from permissionless DAOs to permissioned consortia— alongside their operational realities and limitations. It explores the effectiveness of governance tokens and the vulnerabilities undermining participatory ideals. It further examines whether emerging innovations, such as quadratic voting, market-based, and NFT-based voting mechanisms, mitigate any of the identified issues.
Cyberthreat intelligence sharing is a critical aspect of cybersecurity, and it is essential to understand its definition, objectives, benefits, and impact on society. Blockchain and Distributed Ledger Technology (DLT) are emerging technologies that have the potential to transform intelligence sharing. This paper aims to provide a comprehensive understanding of intelligence sharing and the role of blockchain and DLT in enhancing it. The paper addresses questions related to the definition, objectives, benefits, and impact of intelligence sharing and provides a review of the existing literature. Additionally, the paper explores the challenges associated with blockchain and DLT and their potential impact on security and privacy. The paper also discusses the use of DLT and blockchain in security and intelligence sharing and highlights the associated challenges and risks. Furthermore, the paper examines the potential impact of a National Cybersecurity Strategy on addressing cybersecurity risks. Finally, the paper explores the experimental set up required for implementing blockchain and DLT for intelligence sharing and discusses the curricular ramifications of intelligence sharing.
The unprecedented growth of digital health ecosystems, fueled by electronic health records (EHRs), wearable devices, telemedicine, and AI-driven diagnostics, has amplified the critical need for reliable data provenance mechanisms. Provenance, defined as the comprehensive history of data generation, access, transformation, and transfer, ensures that stakeholders—including patients, clinicians, insurers, researchers, and regulators—can trust the authenticity, integrity, and accountability of healthcare information. Traditional provenance systems, often centralized, are vulnerable to insider manipulation, cyberattacks, data silos, and audit inefficiencies, thereby undermining trust and regulatory compliance. Distributed Ledger Systems (DLS), encompassing blockchain, permissioned ledgers, and Directed Acyclic Graphs (DAGs), offer a paradigm shift by enabling immutable, transparent, and tamper-evident provenance trails across diverse healthcare stakeholders. This manuscript provides an in-depth exploration of DLS-enabled healthcare data provenance by reviewing current literature, identifying research gaps, and developing a methodological framework tested through simulated experiments. Empirical evaluation demonstrates that distributed ledgers reduce provenance validation time by 57–71%, accelerate audit processes by up to 70%, and significantly enhance regulatory traceability under HIPAA and GDPR requirements. Moreover, patient-centric smart contracts and decentralized identifiers foster individual ownership and interoperability, reshaping data governance models toward inclusivity and transparency. While challenges such as scalability, energy efficiency, and privacy-preserving erasure remain, the findings highlight DLS as a transformative infrastructure for establishing trustworthy healthcare ecosystems. The study concludes by recommending hybrid ledger architectures, cryptographic privacy enhancements, and supportive policy frameworks to ensure sustainable, ethical, and globally interoperable healthcare data provenance systems.
Cheick Tidiane Bâ, Benjamin A. Steer, Matteo Zignani, Richard G. Clegg
Blockchain technology and cryptocurrencies have garnered considerable attention over the past 15 years. The term Web3 (sometimes Web 3.0) has been coined to define a possible direction for the web based on the use of decentralisation via blockchain. Cryptocurrencies are characterised by high market volatility and susceptibility to substantial crashes, issues that require temporal analysis methodologies able to tackle the high temporal resolution, heterogeneity, and scale of blockchain data. While existing research attempts to analyse crash events, fundamental questions persist regarding the optimal timescale for analysis, differentiation between long-term and short-term trends, and the identification and characterisation of shock events within these decentralised systems. This article addresses these issues by examining cryptocurrencies traded on the Ethereum blockchain, with a spotlight on the crash of the stablecoin TerraUSD (UST) and the currency LUNA designed to stabilise it. Utilising complex network analysis and a multi-layer temporal graph allows the study of the correlations between the layers representing the currencies and system evolution across diverse timescales. The investigation sheds light on the strong interconnections among stablecoins pre-crash and the significant post-crash transformations. We identify anomalous signals before, during, and after the collapse, emphasising their impact on graph structure metrics and user movement across layers. This article is novel in its use of temporal, cross-chain graph analysis to explore a cryptocurrency collapse. It emphasises the importance of temporal analysis for studies on web-derived data. In addition, the methodology shows how graph-based analysis can enhance traditional econometric results. Overall, this research carries implications beyond its field, for example, for regulatory agencies aiming to safeguard users could use multi-layer temporal graphs as part of their suite of analysis tools.
This paper explores decentralized finance (DeFi), a fast-growing area powered by blockchain technology that offers a new alternative to traditional financial systems. DeFi removes the need for intermediaries like banks, making transactions more transparent, accessible, and often cheaper. This shift not only reduces costs but also helps improve financial access, particularly for people who are underserved by traditional banking systems. Key elements of DeFi, such as smart contracts and oracles, play a central role in automating processes and enabling peer-to-peer exchanges without needing middlemen. Despite its advantages, DeFi faces several challenges. Smart contracts can have security vulnerabilities, oracles may not always provide accurate data, and there is little consumer protection in place, which raises risks for users. Furthermore, DeFi's decentralized and often anonymous structure creates regulatory difficulties, especially when it comes to complying with anti-money laundering (AML) and know-your-customer (KYC) standards, which are crucial for ensuring financial safety and preventing illegal activities. This paper examines these issues and proposes potential solutions, such as decentralized oracle networks, regulatory tools embedded within DeFi platforms, and improved scalability techniques. These solutions aim to enhance DeFi's security while maintaining its core decentralized benefits. The paper concludes by discussing the future of DeFi, stressing the importance of balanced regulations that protect users without stifling innovation. Ultimately, DeFi holds the potential to reshape global finance, making it more inclusive, efficient, and accessible.
Cryptocurrencies have become a significant asset class, attracting considerable attention from investors and researchers due to their potential for high returns despite inherent price volatility. Traditional forecasting methods often fail to accurately predict price movements as they do not account for the non-linear and non-stationary nature of cryptocurrency data. In response to these challenges, this study introduces the Helformer model, a novel deep learning approach that integrates Holt-Winters exponential smoothing with Transformer-based deep learning architecture. This integration allows for a robust decomposition of time series data into level, trend, and seasonality components, enhancing the model’s ability to capture complex patterns in cryptocurrency markets. To optimize the model’s performance, Bayesian hyperparameter tuning via Optuna, including a pruner callback, was utilized to efficiently find optimal model parameters while reducing training time by early termination of suboptimal training runs. Empirical results from testing the Helformer model against other advanced deep learning models across various cryptocurrencies demonstrate its superior predictive accuracy and robustness. The model not only achieves lower prediction errors but also shows remarkable generalization capabilities across different types of cryptocurrencies. Additionally, the practical applicability of the Helformer model is validated through a trading strategy that significantly outperforms traditional strategies, confirming its potential to provide actionable insights for traders and financial analysts. The findings of this study are particularly beneficial for investors, policymakers, and researchers, offering a reliable tool for navigating the complexities of cryptocurrency markets and making informed decisions.
M. M. Khan, Fahd Sikandar Khan, Muhammad Nadeem, Taimur Khan · 6 authors
Blockchain technology has emerged as a transformative solution for secure, immutable, and decentralized data management across diverse domains, including economics, healthcare, and supply chain management. Given its soaring adoption, it is crucial to assess the suitability of various blockchain platforms for specific applications. This study evaluates the performance of Hyperledger Fabric (HF) and private Ethereum (Geth) to analyze their scalability (node count), throughput (transactions per second (TPS)), and latency (measured in milliseconds). A benchmarking tool was developed in-house to assess the execution of key smart contract functions—QueryUser, CreateUser, TransferMoney, and IssueMoney—under varying transaction loads (10–1000 transactions) and network sizes (2–16 node count). The results indicate that HF performs significantly better than private Ethereum in terms of invoke functions, achieving up to 5× throughput and up to 26× lower latency. However, private Ethereum excels in query operations because of its account-based ledger model. While Hyperledger Fabric scales efficiently within moderate transaction volumes, it experiences concurrency limitations beyond 1000 transactions, whereas private Ethereum processes up to 10,000 transactions, albeit with performance fluctuations due to gas fees. The findings offer valuable insights into the strengths and tradeoffs of both platforms, informing optimal blockchain selection for enterprise applications that require high transaction efficiency.
Echezona Uzoma, Joy Onma Enyejo, Toyosi Motilola Olola
The integration of distributed ledger technologies (DLTs) into multi-cloud environments presents a transformative approach to addressing data integrity and transactional security challenges in modern digital infrastructures. This review comprehensively examines the intersection of multi-cloud computing and distributed ledger systems, highlighting their potential to provide decentralized, tamper-proof, and transparent data management solutions across diverse cloud platforms. The paper explores key architectural frameworks, consensus mechanisms, interoperability protocols, and cryptographic models that enable seamless integration while ensuring scalability, reliability, and enhanced security. Furthermore, it analyzes current use cases, such as supply chain management, financial services, and healthcare, where multi-cloud DLT integration mitigates risks of single points of failure, data breaches, and unauthorized access. By identifying emerging trends, technological limitations, and research gaps, this review offers valuable insights into optimizing multi- cloud DLT deployments for robust data integrity and secure transactional processes. The study underscores the growing importance of cross-cloud blockchain interoperability and regulatory compliance in advancing secure and resilient multi- cloud ecosystems.
Sourav Purification, Simeon Wuthier, Jinoh Kim, Ikkyun Kim · 5 authors
Current cellular networking remains vulnerable to malicious fake base stations due to the lack of base station authentication mechanism or even a key to enable authentication. We design and build a base station certificate (certifying the base station's public key and location) and a multi-factor authentication (making use of the certificate and the information transmitted in the online radio control communications) to secure the authenticity and message integrity of the base station control communications. We advance beyond the state-of-the-art research by introducing greater authentication factors (and analyzing their individual security properties and benefits), and by using blockchain to deliver the base station digital certificate offline (enabling greater key length or security strength and computational or networking efficiency). We design the certificate construction, delivery, and the multi-factor authentication use on the user equipment. The user verification involves multiple factors verified through the ledger database, the location sensing (GPS in our implementation), and the cryptographic signature verification of the cellular control communication (SIB1 broadcasting). We analyze our scheme's security, performance, and the fit to the existing standardized networking protocols. Our work involves the implementation of building on X.509 certificate (adapted), smart contract-based blockchain, 5G-standardized RRC control communications, and software-defined radios. Our analyses show that our scheme effectively defends against more security threats and can enable stronger security, i.e., ECDSA with greater key lengths. Furthermore, our scheme enables computing and energy to be more than three times efficient than the previous research on the mobile user equipment.
Blockchain consensus mechanisms have relied on algorithms such as Proof-of-Work (PoW) and Proof-of-Stake (PoS) to ensure network functionality and integrity. However, these approaches struggle with adaptability for decision-making where the opinions of each matter rather than reaching an agreement based on honest majority or weighted consensus. This paper introduces a novel deliberation-based consensus mechanism where Large Language Models (LLMs) act as rational agents engaging in structured discussions to reach a unanimous consensus. By leveraging graded consensus and a multi-round deliberation process, our approach ensures unanimous consensus for definitive problems and graded consensus for prioritized decision problems and policies. We provide a formalization of our system and use it to show that the properties of blockchains are maintained, while also addressing the behavior in terms of adversaries, stalled deliberations, and confidence in consensus. Moreover, experimental results demonstrate system feasibility, showcasing convergence, block properties, and accuracy, which enable deliberative decision-making on blockchain networks.
In financial applications, latency advantages -- the ability to make decisions later than others, even without the ability to see what others have done -- can provide individual participants with an edge by allowing them to gather additional relevant information. For example, a trader who is able to act even milliseconds after another trader may receive information about changing prices on other exchanges that lets them make a profit at the expense of the latter. To better understand the economics of latency advantages, we consider a common-value auction with a reserve price in which some bidders may have more information about the value of the item than others, e.g., by bidding later. We provide a characterization of the equilibrium strategies, and study the welfare and auctioneer revenue implications of the last-mover advantage. We show that the auction does not degenerate completely and that the seller is still able to capture some value. We study comparative statics of the equilibrium under different assumptions about the nature of the latency advantage. Under the assumptions of the Black-Scholes model, we derive formulas for the last mover's expected profit, as well as for the sensitivity of that profit to their timing advantage. We apply our results to the design of blockchain protocols that aim to run auctions for financial assets on-chain, where incentives to increase timing advantages can put pressure on the decentralization of the system.
As the number of decentralized applications and users on Ethereum grows, the ability of the blockchain to efficiently handle a growing number of transactions becomes increasingly strained. Ethereums current execution model relies heavily on sequential processing, meaning that operations are processed one after the other, which creates significant bottlenecks to future scalability demands. While scalability solutions for Ethereum exist, they inherit the limitations of the EVM, restricting the extent to which they can scale. This paper proposes a novel solution to enable maximally parallelizable executions within Ethereum, built out of three self-sufficient approaches. These approaches include strategies in which Ethereum transaction state accesses could be strategically and efficiently predetermined, and further propose how the incorporation of gas based incentivization mechanisms could enforce a maximally parallelizable network.
Blockchain technology has emerged as a disruptive force in the financial sector, offering unparalleled transparency, security, and efficiency in managing digital transactions. Governments around the world are increasingly adopting blockchain to enhance their operational capabilities and address the challenges posed by decentralized cryptocurrencies. This chapter will explore the current utilization and future potential of government-endorsed blockchain frameworks in the cryptocurrency ecosystem. It will examine how these initiatives impact financial transparency, regulatory compliance, and economic inclusivity, while also addressing the challenges and ethical considerations involved. The chapter begins by providing an overview of government blockchain initiatives worldwide, focusing on their application in central bank digital currencies (CBDCs), taxation systems, and anti-money laundering efforts. It then delves into the interplay between these frameworks and decentralized cryptocurrencies, discussing their coexistence and potential synergies. Case studies from pioneering nations, such as China’s Digital Yuan project and Estonia’s blockchain-based e-governance, will illustrate real-world implementations. Looking toward the future, the chapter hypothesizes scenarios for the global adoption of government blockchain in cryptocurrency, considering technological advancements, geopolitical influences, and economic trends. It will critically assess the risks, including potential overreach, surveillance concerns, and barriers to interoperability, proposing actionable recommendations to ensure equitable and sustainable development.
M. Ferreira, Bernardo J. R. Figueiredo, Alexandre Soares dos Santos, João Filipe Matos · 5 authors
Digital twins (DTs) are transforming industries by offering real-time virtual representations of physical assets, enabling smarter decision-making and optimization. However, as these systems become more complex and distributed, maintaining reliable traceability remains a significant challenge. To address this, we propose a multi-context, modular platform that leverages blockchain and distributed ledger technologies (DLTs) to enhance the traceability of digital twins. Our proposal will ensure secure, immutable, and transparent records of data interactions, fostering greater trust, accountability, and interoperability across various domains. The foundation of this work involved identifying the key Architecturally Significant Requirements (ASRs) that must be considered in the platform's design. Based on the first ASRs related to traceability and data flexibility, we developed a conceptual architecture supported by an ontology that addresses the multi-context traceability challenge. The proposed approach was validated through two distinct case studies: livestock management and shop-floor processes. Moving forward, our focus will be on addressing the remaining ASRs that were already identified, to further develop a high-performance, secure, and scalable modular platform capable of supporting diverse contexts and applications.
Modernization of cadastral systems is a continuous process that corresponds to dynamic changes in society and technology. Studying international experience allows us to identify promising areas of development and implementation of innovative solutions in the field of land cadastre. Particular attention is paid to the issues of integrating cadastral systems with other information resources and ensuring the accuracy of geospatial data. This article presents a comparative analysis of the cadastral systems in Ukraine and Switzerland to identify opportunities for improving the Ukrainian land cadastre. The study examines the legal framework, functional purpose, technical characteristics, and financing aspects of both systems. Based on an analysis of Swiss experience, recommendations for modernizing Ukraine’s cadastral system are proposed, including the implementation of decentralized management elements, enhancement of technical infrastructure, and optimization of the financial model. The research highlights the fundamental differences in the cadastral structures of both countries. The Swiss cadastre operates as a decentralized system with significant regional autonomy, ensuring high data accuracy and integration with various geospatial resources. Meanwhile, the Ukrainian cadastral system follows a centralized model, which facilitates uniformity in land registration but faces challenges in data updating and interregional cooperation. The study underscores the importance of implementing 3D cadastres, improving the accessibility of cadastral data, and integrating public-law restrictions into the system, as exemplified by Switzerland. The financial mechanisms supporting the Swiss cadastre are analyzed, emphasizing the advantages of a mixed funding model that combines public financing with elements of self-sufficiency. In contrast, Ukraine relies primarily on state funding, which limits its ability to introduce innovative solutions. The article suggests that adapting Switzerland’s financing approach could improve the efficiency and sustainability of Ukraine’s cadastral system. The study concludes that adopting best practices from Switzerland – such as a more flexible regulatory framework, enhanced geospatial data integration, and diversified financial support – can significantly contribute to the modernization of Ukraine’s land cadastre. Implementing these measures will enhance transparency, facilitate more efficient land management, and improve the overall quality of cadastral services.
Prof. Pritesh Patil, Pranav Dhote, S.S. Kulkarni, Ketan Agrawal
Modern interconnected society creates ongoing challenges to charitable giving because donors need greater assurance of transparency and financial accountability. A new Ethereum-based solution from our research removes intermediaries by establishing an application dedicated to charitable activities. The DApp provides an integrated system for traditional offers and conditional funding structures which operates on blockchain technologies at base level. A framework of Solidity smart contracts connects with React.js frontend components and Ethers.js implements the blockchain communication protocols to deliver a smooth donor transaction process. The platform features milestone-based withdrawals that functions to distribute crowdfunded money after specific campaign targets have been reached thus building transparent reporting. The system gives contributors complete control between funding registered organizations directly and specific projects where each financial transaction is recorded permanently on the blockchain ledger. The unbending nature of blockchain as a record system provides historic visibility for all charitable transactions. Through distributed ledger technology implementation our framework provides donors both simple donation processes and a modern model for reliable philanthropic activities which allow full monitoring of every charitable contribution.
One of the most emblematic theorems in the theory of distributed databases is Eric Brewer’s CAP theorem. It stresses the tradeoffs between Consistency, Availability, and Partition and states that it is impossible to guarantee all three of them simultaneously. Inspired by this, we introduce the new CAP theorem for autonomous consensus systems, and we demonstrate that, at most, two of the three elementary properties, Consensus achievement (C), Autonomy (A), and entropic Performance (P) can be optimized simultaneously in the generic case. This provides a theoretical limit to Blockchain systems’ decentralization, impacting their scalability, security, and real-world adoption. To formalize and analyze this tradeoff, we utilize the IoT micro-Blockchain as a universal, minimal, consensus-enabling framework. We define a set of quantitative functions relating each of the properties to the number of event witnesses in the system. We identify the existing mutual exclusions, and formally prove for one homogenous system consideration, that (A), (C), and (P) cannot be optimized simultaneously. This suggests that a requirement for concurrent optimization of the three properties cannot be satisfied in the generic case and reveals an intrinsic limitation on the design and the optimization of distributed Blockchain consensus mechanisms. Our findings are formally proved utilizing the IoT micro-Blockchain framework and validated through the empirical data benchmarking of large-scale Blockchain systems, i.e., Bitcoin, Ethereum, and Hyperledger Fabric.
Introduction: the study covers features of investigation activities of internal affairs in countering bribery committed with the use of digital financial and cryptocurrency assets. Materials and Methods: the doctrinal law provisions on the investigation activities of the internal affairs in the light of the fight against corruption became the study materials. Regulations on countering bribery committed with digital financial and cryptocurrency assets were the basic study sources. The author used universal (analysis, deduction, and induction) and special (structure logic, dialectical, and legal) methods of cognition. Literature review: the author analyzed investigation and criminology scientific works, as well as considered studies on informational and telecommunication technologies in countering bribery. Thus, he came to the conclusion that H.A. Asatryan, A.P. Dmitrienko, M.G. Zhigas, V.S. Ishigeev, A.V. Kulikov, A.I. Ovchinnikov, A.L. Repetskaya and others contributed substantially to the study. Results: the following conclusions were drawn from the research: - The most challenging issues concerning the detection and documentation of bribery committed using digital financial and cryptocurrency assets were analysed by the author. - The most common ways to identify crypto wallets and their users, which can be used by internal affairs bodies, were considered. - The scheme of criminal transactions related to bribery was presented. - The regularity in the use of information and telecommunication technologies by internal affairs bodies in combating bribery committed using digital financial and cryptocurrency assets was defined. Discussion and Conclusions: there are signs of circulation of digital financial and cryptocurrency assets in bribery. The author presents his own variant of the inquiry for crypto platform to receive necessary information for the investigation; measures to improve investigation efficiency in internal affairs bodies when combating bribery committed with digital financial and cryptocurrency assets.