Alie Ndiaye, Mamadou Ba, Jean Aimé Florent Kikobet Kolodo, S Ouya
This study addresses the critical challenge of securely transmitting digital cheques in blockchain-based agricultural platforms operating under intermittent connectivity constraints, particularly in Guinea, where only 34% of the population has access to the Internet. We propose an innovative protocol that cryptographically embeds the seller’s address into the digital cheque signature, thereby creating an autonomous notification system independent of external communication infrastructures. The approach introduces three key innovations: address-integrated signatures, asynchronous validation protocols, and distributed notification mechanisms operating directly on the blockchain. The experimental implementation employs Ganache as an Ethereum simulator with a React.js DApp interface, enabling buyers to issue cryptographically signed cheques and sellers to automatically receive notifications through blockchain events. The results demonstrate technical feasibility with a secure transfer of 2 ETH validated by balance variations. The protocol ensures integrity, non-repudiation, and resilience to network disconnections, outperforming existing solutions that require stable connectivity. This contribution paves the way for fully autonomous decentralized agricultural markets adapted to the infrastructural constraints of West Africa.
This paper introduces the Universal Turing Market Machine (UTMM): a unified, neuromorphic market infrastructure designed to compute, adapt, and coordinate economic activity autonomously. Building on Hayek’s theory of spontaneous order and Ashby’s Law of Requisite Variety, the paper argues that while markets themselves emerge naturally, the computational substrate that supports them can be intentionally designed. The UTMM integrates sensory inputs (e.g., IoT data), distributed ledger signaling, evolutionary compute layers, and real-world actuators to form an adaptive, nervous-system-like architecture for market coordination. This framework enables transparent, auditable, self-organizing market processes capable of discovering their own requisite dimensionality. The paper formalizes these systems under the term Adaptive Resource-Coordinated Organisms (ARCOs), digital-economic organisms that merge machine learning, blockchain, and adaptive market solvers into a cohesive evolutionary market machine.
Uhryn A.P. FINANCIAL SUPPORT FOR THE DEVELOPMENT OF LOCAL COMMUNITIES IN DEVELOPED COUNTRIES: IMPLEMENTATION IN DOMESTIC PRACTICE Purpose. The aim of the article is to summarise and systematise international experience in financial support for the development of local communities in developed countries and to substantiate the directions for its implementation in domestic practice, taking into account the tasks of strengthening the revenue base of local budgets in Ukraine, increasing the institutional stability of communities and ensuring their sustainable development in the context of post-war recovery and budget decentralization. Methodology of research. The methodological basis of the study is the systemic and institutional approaches, which made it possible to consider local finances as a complex multi-level system in which budgetary, tax, and transfer mechanisms interact within the current institutional environment. In the process of research, comparative analysis methods were used to compare models of local finance organization and mechanisms of fiscal decentralization in different countries, logical generalization to form theoretical conclusions and conceptual provisions, as well as structural and functional analysis to identify the role of individual elements of the budget system in ensuring the financial autonomy of local self-government. Thus, the research methodology is based on a comprehensive combination of modern theoretical and methodological approaches to analysing the functioning of the public finance system in decentralized conditions. The theoretical basis of the work is formed by the provisions of the theory of fiscal federalism, which reveal the patterns of distribution of revenue and expenditure powers between levels of government, the concept of tax autonomy of territorial communities, as well as scientific approaches to inter-budgetary equalization as a tool for ensuring financial capacity and balanced regional development. Findings. It has been established that the effectiveness of financial support for local communities is determined by a balanced combination of tax autonomy, stable own and fixed revenues, as well as effective mechanisms of vertical and horizontal financial equalisation. The institutional features of decentralised, cooperative and centralised models of local finance, their impact on the financial stability of communities and the quality of public services are revealed. It is substantiated that Ukraine's priorities are: strengthening the role of personal income tax and property tax in local budget revenues, improving formula equalisation based on European models, developing municipal investment and project financing instruments, and integrating international aid into the local finance system while maintaining budgetary discipline. The obtained results correspond to the tasks of improving the effectiveness of community’s information and communication resources and strengthening the financial capacity of territories. Originality. International models of financial support for territorial communities have been systematised through the prism of combining tax autonomy and solidarity mechanisms; adaptation guidelines for Ukraine have been substantiated, combining the expansion of communities' own revenue base with the improvement of inter-budgetary relations and the strengthening of the financial responsibility of local self-government bodies. Practical value. The proposed approaches can be used by public authorities and territorial communities of Ukraine to form a sustainable revenue policy, optimise the financial equalisation system, plan development investments and improve the quality of budget management. The research results are relevant to scientific and practical tasks of improving local budget revenue management and introducing strategic risk management into community activities. Key words: financial support for local communities, fiscal decentralization, local budgets, tax autonomy, inter-budgetary relations, financial equalisation, post-war recovery.
Dec 1, 2025·International journal of intelligent computing and information sciences/International Journal of Intelligent Computing and Information Sciences
sarah Osama anis, Mohammed Mabrouk Morsey, Mostafa Aref
In the rapidly evolving landscape of cryptocurrency, gaining a deep understanding of public sentiment has become increasingly essential, especially given the significant impact of social media platforms on market perceptions and trends. This paper introduces a sophisticated sentiment classification model that utilizes a Bi-LSTM architecture to analyse over one million tweets related to Bitcoin. By integrating Explainable AI techniques, particularly LIME (Local Interpretable Model-agnostic Explanations) framework, our model not only achieves an impressive test accuracy of 98% but also offers valuable insights into its decision-making process, making the results more interpretable for users Our findings highlight robust performance metrics across precision, recall, and F1-scores, which collectively underscore the model's reliability and effectiveness in real-world applications. Furthermore, we delve into the opaque nature of the Bi-LSTM model through the application of LIME, which sheds light on how particular words and phrases have a strong impact on sentiment predictions. This research equips future investigations with conceptual frameworks and analytical tools that can be customized to study a broader range of cryptocurrencies. Through this work, we aim to foster a more nuanced comprehension of how public sentiment shapes market behaviour and decision-making in the digital currency space.
A Sowmiya, Kavitha Muthukumaran, V Jhansi, Jesus Milton Rousseau S. · 6 authors
Decentralized Finance (DeFi) represents a transformative shift in the financial landscape by using blockchain technology to enable peer-to-peer services without traditional intermediaries. This study adopts a socio-cultural lens to examine the key factors that influence individuals’ intentions to adopt DeFi technologies. In particular, we explore how performance expectancy (perceived usefulness), effort expectancy (perceived ease of use), social influence, and innovativeness drive user adoption, and how these relationships are moderated by demographic factors such as age, gender, education, and income. Drawing on survey data (N = 425) collected in India (an emerging market context), the research employs Structural Equation Modeling (SEM) to test the proposed framework. Results indicate that perceived usefulness and ease of use are significant positive predictors of DeFi adoption. Social influence and individual innovativeness also encourage adoption, especially among younger and more educated users. Moreover, demographic characteristics shape the strength of these effects: for instance, younger users find DeFi more useful and easier to use, women are more impacted by social recommendations, and higher-income individuals are more inclined to adopt innovative financial solutions. These findings underscore that DeFi adoption is not just a technical or economic process, but a culturally situated phenomenon influenced by social dynamics and user diversity. The paper discusses implications for improving digital financial inclusion and strategies for stakeholders to foster broader DeFi acceptance across different social groups
Blockchain-based decentralized finance (DeFi) is a major financial innovation, enabling transparency and inclusion through programmable rails. The transition to DeFi 3.0 defined by cross-chain interoperability, multichain ecosystems, and tokenized real-world assets (RWAs) broadens functionality yet introduces potential systemic vulnerabilities. Prior research often treats protocol exploits or single risk families in isolation, leaving no unified lens connecting DeFi risks to financial resilience. This study develops a unified DeFi 3.0 risk taxonomy and maps it to resilience capacities. Using a three-lane systematic literature review (peer-reviewed, grey literature, preprints; 2021-2025; 43 sources), we identify twelve risk domains in three categories: technology and data infrastructure; market and economic; and governance, legal, and operational. We then assess resilience along three capacities absorptive (stablecoins, automated market makers/AMMs, insurance), adaptive (regulatory alignment, RWA tokenization, AI integration), and transformative (transparency, inclusion, ESG alignment). The resulting framework operationalizes resilience theory via this taxonomy, providing a structured reference for regulators, developers, and scholars to support innovation while strengthening systemic stability.
Tengku Mohd Diansyah, Nuraminah Ramli, Muzammil Jusoh
This study addresses the limitations of existing decentralized e-voting systems, particularly their reliance on public distributed infrastructures, limited real-world deployment feasibility, and lack of comprehensive evaluation. Previous studies have demonstrated the potential of distributed ledger-based voting mechanisms; however, most focus on conceptual designs or small-scale prototypes without detailed performance and usability validation. To address this gap, this research proposes and implements a decentralized e-voting system deployed on a local server infrastructure using distributed ledger technology and automated validation mechanisms for vote integrity. The system is designed to reduce dependency on external networks while maintaining transparency, immutability, and operational efficiency. The system was evaluated through functional testing, performance analysis, and user acceptance testing involving 30 participants in a controlled environment with 20 simulated voters. The results show that the system achieved a functional accuracy of 96% across 25 test scenarios. The average transaction response time ranged between 0.6 and 1.6 seconds, indicating efficient processing under moderate load conditions. However, the evaluation is limited to small-scale simulations and does not include stress testing, large-scale scalability analysis, or advanced security validation. Therefore, the findings demonstrate system feasibility rather than fully validated effectiveness. These results suggest that decentralized e-voting systems deployed on local infrastructures can provide a practical and efficient solution for controlled election environments, while further research is required to evaluate scalability, security robustness, and real-world deployment readiness.
This paper challenges the prevailing assumption in Central Bank Digital Currency (CBDC) design that comprehensive transaction surveillance is necessary for financial stability and crime prevention. We propose an alternative privacy-preserving architecture that achieves equivalent or superior fraud detection through mechanism design rather than identity monitoring. Key contributions: Separation of pattern detection from identity: Transaction graph analysis identifies structural anomalies without accessing participant identities Transaction-level intervention: Suspicious activity flags individual transactions, not accounts or users Opt-in deanonymization: Identity revelation is always voluntary; users may abandon flagged transactions without consequence Architectural enforcement: Privacy guarantees are structural, not policy-dependent The framework inverts the burden of proof in financial surveillance. Rather than requiring users to demonstrate legitimacy, it requires the system to demonstrate suspicion—and even then, users retain the option to walk away. This creates a game-theoretic deterrent where illicit actors cannot complete transactions, while legitimate users experience minimal friction. We demonstrate that privacy-preserving CBDC architecture is technically feasible using established cryptographic primitives (zero-knowledge proofs, secure multi-party computation, threshold cryptography) and that the choice to implement surveillance infrastructure represents a policy decision rather than technical necessity. Part of the Adversarial Systems Research program investigating friction dynamics in complex systems where competing interests generate structural conflict.
The growth of cloud computing in the healthcare field has led to significant developments, but ensuring the confidentiality and protection of medical records such as electronic health records (EHRs) remains a major concern for healthcare service applications. In cloud computing, the basic authentication provided by most service providers is insufficient to ensure secure access to critical or sensitive resources. Moreover, most of the existing healthcare management systems are ineffective in handling a number of patient data, which leads to single points of failure. To address these issues, elliptic curve cryptography (ECC) with Curve25519 is utilized to enhance security in cloud storage, particularly within healthcare management systems. The ECC with Curve25519 is optimized for efficient and fast scalar multiplication, which reduces computational overhead and enhances performance. The curve parameters are selected to prevent vulnerabilities and ensure security against known attacks. Moreover, it is efficient in maintaining the integrity of patient records, which reduces storage and bandwidth requirements. The ECC with Curve25519 achieves lower Key-Gen, prove, verify, proving key size, and verification key size of 13.7 s, 48 s, 0.608 s, 13.27 Mb, and 123.70 Kb, respectively, in comparison with proxy re-encryption algorithm with zero-knowledge proof (ZKP).
Chi Zhang, Fenhua Bai, Xiaohui Zhang, Jinhua Wan · 6 authors
As a middleware technology in distributed computer systems, blockchain systems represent a paradigm for achieving node interconnectivity. Despite this, technical differences between various blockchain networks have led to the emergence of a phenomenon known as multi-chain, where inter-chain communication has become a trust barrier. Cross-chain technology is a powerful tool that allows data to flow between different blockchain networks, breaking down data barriers and enabling seamless data transfer. However, cross-chain identification may lead to potential risks such as the exposure of private information and data loss or tampering. In this brief, we propose Universal Cross-Chain Permissioned Blockchain (UCCPB) architecture, which connects single permissioned chains into a multi-chain system. Based on this, the Cross-Chain Anonymous Identity Authentication (CCAIA) model is proposed, which implements privacy-preserving chain identity registration and verification through zero-knowledge proof without a trusted setup. Furthermore, we propose the Proof of Cross-Chain Invocation (PoCI) mechanism of UCCPB, which consists of a node election and consensus on the invocation result. This mechanism ensures the correctness of the cross-chain invocation results and incentivizes nodes to participate in UCCPB. Our experiments show that the proposed UCCPB achieves a balance between performance and privacy while improving the security of cross-chain invocations.
Sana Ullah, Syed Muslim Jameel, Meghann Drury-Grogan, Mara Sintejdeanu · 5 authors
The complexity of cross-border regulatory compliance in the MedTech sector imposes significant administrative and financial burdens on manufacturers, characterized by manual processes, data redundancy, and country-specific, cross-border heterogeneous regulations. To address this, we present EireLedger, a decentralized framework that automates and cryptographically enforces regulatory compliance verification. EireLedger utilizes a novel dual-purpose zero-knowledge proof (ZKP) scheme, instantiated with Groth16 zk-SNARKs, which allows a manufacturer to prove a device dossier's compliance to a jurisdiction-specific regulator in a privacy-preserving manner, while simultaneously generating a verifiable ZKP-based access grant for the regulator. This cryptographic proof is immutably anchored to a permissioned Hyperledger Fabric blockchain, which orchestrates the protocol and maintains a minimal, auditable record. The corresponding encrypted dossier artefacts are stored off-chain in a private IPFS cluster. Our comprehensive evaluation demonstrates that on-chain proof verification is highly efficient with a median latency of 12.3 ms, and our integrated ZKP-as-access-control model reduces end-to-end audit latency by 40% compared to traditional attribute-based access control (ABAC) by eliminating external authorization calls. The on-chain storage footprint is constant at ~2.1 KB per audit, ensuring data minimization. The framework also supports right to erasure in compliance with GDPR, cryptographically unpinning a 5 GB dossier in under 90 s. These results establish EireLedger as a novel, privacy-preserving, and practical solution for cross-border regulatory compliance in the MedTech supply chains.
Blockchain Technology Applications and Security
Big Data and Digital Economy
Physical Unclonable Functions (PUFs) and Hardware Security
Dobrotă Gabriela, DAN NICOLETA, BUTĂNESCU-VOLANIN REMUS-CONSTANTIN
Public finance sustainability represents a fundamental pillar of macroeconomic stability and a key determinant of the ability of states and local communities to cope with major economic shocks. Against the backdrop of successive crises over the past two decades—financial, health-related, and geopolitical—the relationship between fiscal sustainability and community resilience has gained increasing attention in both economic scholarship and European institutional debates. The aim of this article is to examine the linkage between fiscal sustainability and the resilience of local communities through an integrated approach that combines cross-country analysis at the European Union level with an in-depth assessment of Romania’s experience. The study relies on Eurostat data covering the period 2015 2023 and focuses on fiscal indicators, the degree of fiscal decentralization, and the capacity of local communities to translate public resources into economic and institutional resilience. The methodological framework includes descriptive and comparative analysis, alongside the construction of a composite Community Resilience Index. The empirical findings reveal substantial disparities across EU Member States and indicate that fiscal sustainability, when accompanied by functional fiscal decentralization and strategically oriented public investment, is associated with higher levels of community resilience. In the case of Romania, the gap between a relatively moderate level of public debt and comparatively low community resilience is largely explained by limited local fiscal autonomy and persistent institutional constraints.
Crowdfunding for social goods has become a transformative force in India's development ecosystem, emerging as a crucial citizen-driven financing model for healthcare assistance, educational support, social welfare, environmental conservation, and community development projects.As India progresses toward achieving the United Nations Sustainable Development Goals (SDGs), the importance of innovative, decentralized, and participatory funding mechanisms has grown significantly.Traditional sources of funding-government schemes, philanthropic donations, CSR initiatives, and institutional grants-are often insufficient to meet the enormous financial needs of low-income and marginalized communities.In this context, digital crowdfunding platforms such as Ketto, Milaap, ImpactGuru, Donatekart, and GiveIndia offer flexible, inclusive, and accessible channels for mobilizing public contributions.Unlike commercial crowdfunding, donation-based crowdfunding provides no financial returns to donors.Therefore, donors' decisions are fundamentally shaped by behavioural finance factors rather than economic incentives.This research adopts a behavioural finance perspective to examine the psychological, emotional, cognitive, and social determinants that influence campaign success for SDG-aligned social crowdfunding projects in India.The study investigates how donor motivations-including altruism, empathy, moral obligation, warm-glow effect, identity-driven giving, and social influence-interact with campaign design elements, platform architecture, and trust signals to determine fundraising outcomes.Findings from prior research and platform-level data indicate that trust remains the strongest driver of donation intention.Indian donors tend to be risk-averse due to concerns about fraud, misrepresentation, and misuse of funds.As a result, trust-building mechanisms-such as verified fundraisers, authentic documentation, medical proof, transparent financial breakdowns, institutional endorsements, and frequent campaign updates-significantly increase credibility and donor confidence.Emotional storytelling is another powerful determinant; campaigns featuring identifiable beneficiaries, vivid visuals, personal narratives, and urgent medical needs evoke stronger empathy and are more likely to attract support.Social proof and herding behaviour also play a critical role.Donors frequently look to the actions of others to validate campaign legitimacy, especially when information is limited.High engagement metrics-number of donors, comments, shares, early contributions-signal popularity and urgency, triggering positive herding effects that accelerate the fundraising process.Campaigns that achieve early momentum typically experience higher visibility, stronger network effects, and higher conversion rates.In India, where community networks, family ties, religious identity, and regional affiliations are strong, such social cues significantly enhance campaign reach:
The global Smart Contract Market was valued at USD 1.83 billion in 2023 and is projected to reach USD 7.78 billion by 2030, growing at a CAGR of 23.0% from 2024 to 2030. Smart contracts are self-executing agreements encoded on blockchain platforms that automatically enforce contractual terms when predefined conditions are met, reducing intermediaries and transaction costs. The market spans multiple sectors, including BFSI, healthcare, real estate, transportation, and government services. Growth is driven by the increasing adoption of blockchain in financial institutions, rising cybersecurity threats, and initiatives for digital asset management. Market restraints include high development and auditing costs, alongside limited flexibility. Innovations in scalability solutions and AI integration are expected to expand market potential, making smart contracts more robust, efficient, and widely deployable. This manuscript provides a comprehensive analysis of market dynamics, segmentation, regional trends, and competitive landscape of the smart contract industry.
Abstract The digital transformation of global supply chains presents unprecedented opportunities, yet it concurrently exacerbates the existing gap in financial inclusion for Micro, Small, and Medium Enterprises (MSMEs). Traditional supply chain finance (SCF) models often fail to serve these small suppliers due to high information asymmetry, lack of verifiable collateral, and manual, paper-intensive processes, leading to significant liquidity constraints. This study proposes and empirically investigates blockchain technology as a foundational solution to mitigate these challenges. Specifically, it examines how blockchain-enabled traceability fosters greater trust and transparency, which in turn facilitates more accessible and inclusive supplier financing mechanisms. Employing a mixed-method approach (Quantitative N=150−180 survey and Qualitative interviews) with a cross-sectional design, the research analyzes relationships using descriptive statistics, regression, and factor analysis. Preliminary findings are expected to demonstrate a significant positive impact of blockchain adoption on financial inclusion metrics for MSMEs. The research contributes by providing a rigorous framework for practitioners and policymakers aiming to leverage decentralized technology to create a more equitable and sustainable global trade ecosystem. Keywords: financial inclusion, blockchain enabled supply, micro, small, and medium enterprises,
Academic credential fraud and falsification of research outputs remain persistent challenges in higher education and research communities. Traditional centralized credential verification systems are vulnerable to tampering, slow verification processes, and lack of transparency. This research introduces a robust blockchain-based consortium framework for transparent and tamper-proof verification of academic credentials and research outputs. Unlike prior works that primarily address identity or degree validation, our system integrates universities, accreditation authorities, and publishers into a multi-layered consortium blockchain, ensuring trust among multiple stakeholders. To preserve privacy, zero-knowledge proofs (ZKPs) are applied, enabling credential verification without disclosing sensitive personal data. The framework also introduces a dynamic revocation mechanism to handle fraudulent, plagiarized, or revoked certificates and publications. A prototype implementation on Hyperledger Fabric demonstrates feasibility, achieving high throughput (182 TPS), low latency (1.2 s average block confirmation), and efficient scalability with multiple nodes. Our results highlight the potential of blockchain in building a global, tamper-proof, privacy-preserving academic verification ecosystem, addressing credential fraud and ensuring research integrity.
Resumo / Abstract : Este artigo pretende demonstrar como o Bitcoin se insere na construção de uma cultura de paz. Apresenta a evolução do conceito, de “não guerra” para “não violência”, e caracteriza a cultura de paz como uma dinâmica social de colaboração. Pontua que as transações não mediadas por terceiros possibilitam que os indivíduos escapem da influência econômica que acentua a assimetria de poder. Reconhece que a dinâmica que recompensa e incentiva a integridade da rede bitcoin privilegia a colaboração. Ao final, conclui que estamos diante de uma infraestrutura monetária que possibilita aquilo que queremos ver acontecer. This paper aims to demonstrate how Bitcoin fits into the construction of a culture of peace. It presents the evolution of the concept, from "non-war" to "non-violence," and characterizes the culture of peace as a social dynamic of collaboration. It points out that transactions not mediated by third parties allow individuals to escape the economic influence that accentuates power asymmetry. It recognizes that the dynamic that rewards and encourages the integrity of the Bitcoin network prioritizes collaboration. In conclusion, it states that we are facing a monetary infrastructure that enables what we want to see happennig.
In the context of economic globalization and rapid internet development, emerging digital technologies such as cloud computing, big data, and AI are revolutionizing industry production and sales. Smart Contracts, particularly empowered by blockchain advancements, present promising prospects. However, traditional contracts remain dominant in economic activities, especially in China’s vast SME market, where risks of real world transaction instability hinder smart contract adoption. Technical vulnerabilities and ecological security issues in smart contract platforms pose challenges in translating legal language into code. Despite progress in natural language processing, translating legal documents accurately remains difficult, burdening judges and programmers with time costs. Therefore, research on smart contract architecture and legal applications, along with practical solutions, is imperative for both theoretical and practical advancements.
Smart contracts are digital protocols programmed on the blockchain network that automatically execute agreements once pre-defined conditions are met, without human intervention.These contracts are characterized by transparency, speed, and security, as they are stored and documented on a network that cannot be easily modified.Smart contracts rely on software code that defines conditions and procedures, making their implementation precise but also irreversible or easily modified after publication. They are used in several fields, including decentralized finance (DFI), supply chain management, and digital healthcare.Despite these advantages, smart contracts face fundamental challenges, most notably software vulnerabilities that can be exploited by attackers due to the lack of a clear legal framework in many countries, the difficulty of interpreting human intentions through software code alone, and the limited ability of smart contracts to handle exceptional or complex situations.The research topic will be divided into a research plan consisting of an introduction, a section, and two sections.The first section addresses the concept of smart contracts, while the second section explains the legal status of smart contracts in civil law.
Edison A. Arteaga López, Gustavo A. Ramírez González, Carlos Alberto Astudillo
The growth of the Internet of Things (IoT) has highlighted the limitations of centralized data platforms, particularly in terms of security and scalability. Distributed Ledger Technologies (DLT) offer a solution, but traditional DLT architectures, such as blockchain, are often incompatible with low-power wireless IoT networks (LPWAN) due to their latency and operational cost. This paper presents a comparative and empirical performance analysis of two end-to-end data oracle systems designed to record data from a LoRaWAN sensor network. The first implementation uses IOTA Tangle, while the second is based on a blockchain compatible with the Ethereum Virtual Machine (EVM). By evaluating key indicators such as latency and transaction costs, our results demonstrate that the IOTA system offers significant superiority, with a predictable median latency of 4.47 seconds and transaction costs that are economically negligible. In contrast, the blockchain implementation incurred measurable gas costs and demonstrated an architecture with inherently higher and extremely unpredictable latency, with a median of 11.52 seconds and outliers exceeding 200 seconds. We conclude that the IOTA Tangle architecture is technologically and economically better prepared to support scalable and sustainable IoT applications over wireless infrastructures.
This chapter explores the extent of the complex relationship between cryptocurrency and unexplained wealth, emphasizing the dual nature of these digital assets as both tools for legitimate wealth accumulation and facilitators of financial crime. Despite their potential for investment and trading, cryptocurrencies have been implicated in significant criminal activities, with estimates indicating that nearly 46% of Bitcoin transactions involve illicit behaviour. This analysis delves into the mechanisms by which cryptocurrencies allow for wealth accumulation – ranging from investing in volatile markets to participating in initial coin offerings – while examining the inherent risks of anonymity, decentralisation, and minimal regulatory oversight that attract criminal actors. Furthermore, the paper discusses how these features enable market manipulation and facilitate illegal trade on dark web platforms. Additionally, this chapter discusses how cryptocurrencies enable wealth accumulation and offer mechanisms for obfuscating wealth, mainly through privacy coins like Monero and Zcash. These coins incorporate advanced encryption techniques, such as ring signatures, stealth addresses, and zero-knowledge proofs, which complicate efforts by law enforcement to trace transactions and identify users. Ring signatures obscure the identity of transaction signers, while stealth addresses disconnect the sender and receiver, ensuring anonymity. Zero-knowledge proofs provide verification without revealing sensitive information, enhancing confidentiality further. Finally, tumbling and mixing services aggregate multiple users’ transactions, obscuring the financial trail and making asset recovery exceedingly difficult.
Abstract A hybrid lattice-based commitment scheme is proposed for anonymous proofs between hidden values. The method is based on a modification of the BDLOP zero-knowledge proof (ZKP) scheme by replacing the learning with errors (LWE) problem with a learning with rounding (LWR) problem, which theoretically makes it possible to reduce the size of the parameters and reduce the complexity of parameter selection. It is shown that the proposed scheme preserves the property of additive homomorphism, which makes it possible to apply it to prove linear relations. The obtained results can be applied to construct electronic voting protocols or conduct anonymous transactions.