Real world asset tokenization (RWA) introduces programmable finance on chain tools to the market, while bringing cash like returns. This paper focuses on token treasury bond funds to explore whether they are re anchoring the yield benchmark of decentralized finance (DeFi). The key entry point of the study is to build a de facto "interest rate corridor", which is formed by DeFi's stable monetary loan interest rate around the volatility of token treasury bond yield. The research results show that due to the widespread risk exposure in the tokenized currency market, DeFi USD returns have gradually converged towards short-term interest rate benchmarks. What is more noteworthy is that its stay time in the narrow corridor centered on the yield of token treasury bond is significantly prolonged. This re anchoring effect not only narrows the long-standing divergence between cryptocurrency native interest rates and monetary policy benchmarks, but also reshapes the incentive mechanism for liquidity supply, and further tightens the integration channels between on chain markets and traditional fixed income markets on this basis.
K. Myrzabekkyzy, G. Lukhmanova, B. Dosanov, A. Bolganbayev ¡ 5 authors
This article, within the context of modern financial technology development, analyzes the impact of decentralized finance (hereafter - DeFi) on the traditional financial system and its criminal-risk aspects. The study aims to describe DeFi operating mechanisms (decentralized architecture and smart contracts), systematize the directions of change in banking, lending, insurance, and investment services, and identify the main types of misconduct and fraud while proposing preventive measures. The paper clarifies DeFiâs operational features, the role of smart contracts, and the nature of decentralization, and examines DeFiâs position across traditional financial service segments. Types of offenses and fraudulent schemes occurring on DeFi platforms are identified, and prevention measures are proposed. A comparison between DeFi and traditional finance is provided, highlighting key advantages and disadvantages and offering recommendations to reduce criminal risks.
Decentralized authentication in dynamic mobile networks faces significant challenges due to high node mobility, resource constraints, and vulnerabilities to side-channel attacks. In this work, we present MobiAuth , a blockchain-driven framework based on Hyperledger Iroha and OMNET ++ that enables secure, peer-to-peer authentication using compact Ed25519 signatures and ephemeral session keys. Our protocol eliminates single points of failure by distributing trust across a permissioned ledger and employs constant-time cryptographic operations to thwart timing and power-analysis attacks. We validate MobiAuth through co-simulation in OMNET ++ integrated with Iroha via a Python gRPC bridge and benchmark its performance with Hyperledger Caliper. Simulation yields 95% packet delivery with an authentication latency ranging from 12 ms in the only OMNeT ++ and baseline to 20â150ms in the full ledger-integrated system, and a ledger write throughput of 250tps. Comparative experiments demonstrate a 33% reduction in communication overhead and robust operation under random Control Point failures and Byzantine Access Node behavior. Analysis of on-device ledger synchronization further highlights practical storage growth and bandwidth requirements for long-term deployment. These results indicate that MobiAuth achieves strong security and privacy with modest energy impact, scalable performance, and compatibility with mobile devices in real-world network environments. ⢠Vulnerabilities of mobile network devices in a dynamic environment. ⢠Blockchain-based automatic authentication for mobile devices. ⢠Enhanced security and privacy with Ed25519 curve cryptography. ⢠OMNET++ simulation on Hyperledger Iroha for mobile network. ⢠Protocol verification using Scyther for testing security protocol strength.
Abstract Purpose The purpose of this study is to adapt a Bayesian dualâvirtual nonâcontrast (VNC) method by integrating prior anatomical knowledge from AIâbased multiâorgan segmentation and to generalize it for spectral photonâcounting CT (PCCT) with an arbitrary number of energy channels. Methods A previously proposed Bayesian VNC method is reformulated for any number of energies and adapted for integration with AI segmentation. TotalSegmentator, an openâaccess wholeâbody AI segmentation model, is used to provide spatial priors. The method is applied to simulated contrastâenhanced dualâenergy CT (DECT) and PCCT datasets from eight virtual patients, with and without AI segmentation. Key radiotherapyârelevant parameters such as electron density () and proton stopping power ratio (SPR) are estimated and compared to ground truth values. Additional results are obtained for nonâcontrast scans by setting contrast agent uptake to zero. Results AIâbased segmentation improved the accuracy of parameter estimation for both DECT and PCCT, with a more pronounced effect for PCCT. The combination of high spectral resolution and anatomical priors led to reduced RMS errors in SPR and . Mean absolute waterâequivalent path length (WEPL) errors confirmed the superiority of segmentationâassisted PCCT over other methods. Conclusion This proof of concept demonstrates a flexible, AIâassisted Bayesian framework for extracting quantitative information from contrastâenhanced spectral CT. By integrating AI segmentation and generalizing to PCCT, the method shows improved tissue characterization, suggesting the value of AI in extracting quantitative information beyond DECT. Further validation on clinical datasets is needed. Background Quantitative VNC methods offer the potential to extract radiotherapyârelated parameters from contrastâenhanced spectral CT without the need for additional nonâcontrast imaging. However, the inherently illâposed nature of tissue characterization from limited spectral data remains a major limitation, which requires advanced techniques.
Ethereum is currently the main blockchain ecosystem providing decentralised trust guarantees for applications ranging from finance to e-government. A common criticism of blockchain networks has been their energy consumption and operational costs. The switch from Proof-of-Work (PoW) protocol to Proof-of-Stake (PoS) protocol has significantly reduced this issue, though concerns remain, especially with network expansions via additional layers. The ERC-4337 standard is a recent proposal that facilitates end-user access to Ethereum-backed applications. It introduces a middleware called a bundler, operated as a third-party service, where part of its operational cost is represented by its power consumption. While bundlers have served over 500 million requests in the past two years, fewer than 15 official bundler providers exist, compared to over 100 regular Ethereum access providers. In this paper, we provide a first look at the active power consumption overhead that a bundler would add to an Ethereum access service. Using SmartWatts, a monitoring system leveraging Running Average Power Limit (RAPL) hardware interfaces, we empirically determine correlations between the bundler workload and its active power consumption.
Abstract Decentralized Autonomous Organizations (DAOs) promise to transform governance through blockchain-enabled transparency and communal decision-making. However, unresolved legal responsibilities and speculative governance token dynamics complicate their ability to maintain trust, encourage participation, and secure legitimacy. Drawing primarily on Social Capital Theory (SCT), this study shows how bonding, bridging, and linking social capital intersect with liability ambiguities and token concentration to undermine institutional confidence and grassroots engagement. Public Goods Theory (PGT) clarifies how free-rider tendencies can deter infrastructural support, while Principal-Agent Theory (PAT) highlights incentive misalignments when whales prioritize short-term gains over collective welfare. Through a theoretical lens, this study illuminates how token-based power asymmetries, a lack of regulatory clarity, and conflicting motivations strain the viability of DAOs in fulfilling the promise of decentralized governance. In synthesizing these frameworks, this study advocates tailored governance strategies, ranging from reputation-based voting models to legally compliant organizational wrappers, to mitigate power imbalances, foster inclusive decision-making, and ultimately strengthen DAOsâ resilience in an evolving blockchain ecosystem. By bridging the sociological, economic, and legal perspectives, this study illustrates the interplay of trust, accountability, and incentives that shape DAO sustainability.
Shwetha K R, Divya G S, Bhavan Pande, Darshan K ¡ 6 authors
Due to the ever-increasing demand to use safe and reliable electronic votes, a blockchain-based secure voting system has been developed to enhance transparency, trustfulness, and voter recognition. This system eliminates such issues as voting fraud, impersonation, and manipulating the results by means of biometric verification and decentralized blockchain ledger. The voters are matched to a facial-recognition database containing previously registered voters before voting. It is authenticated by a K-Nearest Neighbors (KNN) approach as it works well on classifying facial features and is not very laborious. After the vote is successfully authenticated, it is stored and signed on a blockchain network where it cannot be altered by another party. The features of smart contracts ensure the safety of voting, the correct counting of votes, and the awareness of each network node of what is happening. The cryptography of hashing and decentralized make certain that the votes are immutable, due to the decentralized structure of blockchain and consensus mechanisms. The face-matching module ensures that only the qualified individuals are allowed to vote. The system also supports mass elections and guarantees the ease of interaction among the voters. It was designed in such a way that it is scalable and user friendly. Trust, security, and efficiency are enhanced in the system through biometrical authentication, distributed ledger technology, encryption, and classification through machine-learning. It is highly dependable in how to conduct the current digital elections.
Wiwit Prawitri, Laras Angelia Nnirwan, Elman Azizov
This research explores the implementation of a blockchain-based forensic audit framework designed to enhance the detection and investigation of suspicious financial activities within decentralized finance (DeFi) ecosystems. The main problem addressed in this study concerns the inefficiency, lack of transparency, and vulnerability to data manipulation commonly found in traditional forensic auditing systems. The objective is to develop a model that integrates blockchain technology with graph-based anomaly detection to improve accuracy, transparency, and scalability in financial audits. The proposed method combines blockchainâs immutable ledger capabilities with automated detection algorithms and Chain of Custody (CoC) verification to ensure data integrity and accountability. The results demonstrate that the proposed system achieves a detection accuracy exceeding 90%, as presented in Table 1, and effectively categorizes different suspicious transaction patterns illustrated in Figure 2. Compared to conventional methods, the framework offers superior performance in terms of speed, reliability, and adaptability. The findings suggest that this approach establishes a new paradigm in forensic auditing by combining automation, transparency, and scalability into a cohesive analytical model. In conclusion, the study confirms that blockchain-based forensic auditing significantly enhances digital financial oversight and provides a foundation for developing intelligent, tamper-proof audit systems suitable for the evolving landscape of decentralized finance.
Abstract The socio-economic developments and the volume of Decentralized Autonomous Organizations (âDAOâ) are increasing day by day. However, debates in the field of law regarding the DAOs are still vigorous. One of the most crucial issues pertaining to DAOs is liability, which is related to their legal nature. Hence, this work first briefly reveals the current liability regime of DAOs within the context of the current landscape of German and Turkish Company Law. Particularly ordinary partnerships, joint-stock companies and limited companies will be examined. Then, the new liability regime for DAOs will be proposed, as a part of the recommendation of a âNew Codeâ. Finally, this work will be concluded with the outcomes and recommendations.
The rising importance of cryptocurrencies as financial assets pushed their applicability from an object of speculation closer to standard financial instruments such as loans. In this work, we initiate the study of secure protocols that enable fiat-denominated loans collateralized by cryptocurrencies such as Bitcoin. We provide limited-custodial protocols for such loans relying only on trusted arbitration and provide their game-theoretical analysis. We also highlight various interesting directions for future research.
Hasan Akgul, Mari Eplik, Javier Rojas, Aina Binti Abdullah ¡ 5 authors
ZK-SenseLM is a secure and auditable wireless sensing framework that pairs a large-model encoder for Wi-Fi channel state information (and optionally mmWave radar or RFID) with a policy-grounded decision layer and end-to-end zero-knowledge proofs of inference. The encoder uses masked spectral pretraining with phase-consistency regularization, plus a light cross-modal alignment that ties RF features to compact, human-interpretable policy tokens. To reduce unsafe actions under distribution shift, we add a calibrated selective-abstention head; the chosen risk-coverage operating point is registered and bound into the proof. We implement a four-stage proving pipeline: (C1) feature sanity and commitment, (C2) threshold and version binding, (C3) time-window binding, and (C4) PLONK-style proofs that the quantized network, given the committed window, produced the logged action and confidence. Micro-batched proving amortizes cost across adjacent windows, and a gateway option offloads proofs from low-power devices. The system integrates with differentially private federated learning and on-device personalization without weakening verifiability: model hashes and the registered threshold are part of each public statement. Across activity, presence or intrusion, respiratory proxy, and RF fingerprinting tasks, ZK-SenseLM improves macro-F1 and calibration, yields favorable coverage-risk curves under perturbations, and rejects tamper and replay with compact proofs and fast verification.
Optimistic responsiveness -- the ability of a consensus protocol to operate at the speed of the network -- is widely used in consensus protocol design to optimize latency and throughput. However, blockchain applications incentivize validators to play timing games by strategically delaying their proposals, since increased block time correlates with greater rewards. Consequently, it may appear that responsiveness (even under optimistic conditions) is impossible in blockchain protocols. In this work, we develop a model of timing games in responsive consensus protocols and find a prisoner's dilemma structure, where cooperation (proposing promptly) is in the validators' best interest, but individual incentives encourage validators to delay proposals selfishly. To attain desirable equilibria, we introduce dynamic block rewards that decrease with round time to explicitly incentivize faster proposals. Delays are measured through a voting mechanism, where other validators vote on the current leader's round time. By carefully setting the protocol parameters, the voting mechanism allows validators to coordinate and reach the cooperative equilibrium, benefiting all through a higher rate-of-reward. Thus, instead of responsiveness being an unattainable property due to timing games, we show that responsiveness itself can promote faster block proposals. One consequence of moving from a static to dynamic block reward is that validator utilities become more sensitive to latency, worsening the gap between the best- and worst-connected validators. Our analysis shows, however, that this effect is minor in both theoretical latency models and simulations based on real-world networks.
This paper proposes Atomic Ownership Blockchains (AOB), a novel blockchain architecture designed to address scalability and decentralization challenges in distributed ledger systems. AOB introduces an approach where each atomic object is represented by an independent blockchain, potentially allowing for horizontal scaling and enhanced security. The system stores only ownership transfer records, which may enable parallel transaction processing and improved throughput. By eliminating traditional mining and voting mechanisms, AOB aims to mitigate certain security risks while proposing an implicit consensus mechanism for resolving forks. The AOB architecture could potentially support the digitization of real-world assets and enable decentralized applications involving shared or fractional ownership. This paper presents the theoretical framework of AOB, discussing its potential advantages and outlining areas for future research and empirical validation. Practical implementation and rigorous testing are necessary to fully assess its viability and impact on digital ownership paradigms.
Decentralized finance (DeFi) lending platforms have rapidly evolved within financial markets, with stablecoins playing a pivotal role in these ecosystems by providing price stability and enhancing capital efficiency. However, DeFi lending platforms still face challenges including market volatility, smart contract security, regulatory uncertainty, and liquidity constraints. This paper analyzes the function of stablecoins within DeFi lending platforms, explores their advantages and challenges, and forecasts future development trends. The article first introduces the fundamental concepts and classifications of stablecoins, then analyzes their advantages and challenges within lending markets, and finally looks ahead to innovations and future developments for stablecoins. Through this analysis, the paper provides in-depth insights for researching stablecoin applications in DeFi lending.
Cheap energy, absence of regulations on mining, low taxes, free industrial zones made Georgia an attractive place for Bitcoin mining and home to such big companies as Bitfury and Binance. This paper asks how and why Georgia become a crypto mining hub and examines crypto mining in relation to the neoliberal state and its economic development mode. This study frames crypto currency mining as a state facilitated development project, which is embedded in Washington Consensus (WC) liberalization and deregulation policies and is enabled by Wall Street Consensus (WSC) derisking policies. The paper argues that crypto currencies - once emerged on allegedly nonpolitical economic grounds to challenge the state and existing financial order - need the state and its sovereign space. The study also unfolds continuities between WC and WSC and demonstrates the destructive character of crypto mining. The paper thus challenges the claims of the crypto industry of being against the state and traditional financial system, provides insights into the political economy of Bitcoin from a peripheral country perspective and enriches ongoing debates on neoliberal derisking states.
The article provides a comprehensive analysis of the constitutional and legal aspects of digital intellectual property in the context of the development of the information society and Ukraine's accelerated digital transformation under wartime conditions.It examines the impact of emerging technologies, particularly artificial intelligence (AI), blockchain, and non-fungible tokens (NFTs), on the transformation of traditional concepts of authorship, ownership, and creative freedom.Special attention is paid to the need for reinterpreting constitutional guarantees enshrined in Articles 41 and 54 of the Constitution of Ukraine through the lens of technological neutrality and contemporary digital realities.The study focuses on the challenges of identifying authorship in works generated with the use of artificial intelligence, as well as on the legal nature of ownership rights to digital assets, including NFTs.It also analyzes the role of the Constitutional Court of Ukraine in shaping the doctrine of digital rights and adapting constitutional interpretation to the challenges of the digital era.Particular emphasis is placed on the importance of digital intellectual property for Ukraine's post-war recovery, especially in the context of developing a national Digital IP Strategy aligned with European approaches and initiatives.The article substantiates the conclusion that the constitutional modernization of intellectual property law is necessary to ensure a balance between human rights, technological innovation, open access to knowledge, and national resilience.Such an approach will contribute to the harmonization of Ukraine's legal system with European and international standards while preserving the human-centered nature of legal regulation in the field of creative activity in the digital age.
Open access
Legal, Health, Environmental and COVID-19 Challenges
Abstract Agile fosters speed, autonomy, and innovation at the team level, but organizations often struggle to preserve these strengths as they scale. Coordination overhead increases, decision-making slows, and the agility that once fueled success begins to erode. This paper introduces an approach to scaling by drawing on Robotics Subsumption Architecture , a model originally developed to build adaptive, autonomous robots. Building on the late Mike Beedle âs pioneering work in applying these robotics principles to organization design , we reimagine how to design systems that grow without sacrificing local autonomy or real-time responsiveness. This approach offers scalable agility by embedding sensing, decision-making, and action into every layerâresulting in organizations that are resilient, decentralized, and capable of surviving todayâs VUCA market.
ABSTRACT Cryptocurrency, a decentralized digital asset enabled by blockchain technology, has transformed global finance by introducing novel mechanisms for value exchange, security, and governance. This comprehensive academic review synthesizes current knowledge across multiple dimensions: the technical foundations of cryptocurrencies (including distributed ledger technologies, cryptographic primitives, and consensus mechanisms), economic and financial implications (market behavior, monetary policy interactions, speculation, and investment risk), legal and regulatory frameworks (jurisdictional approaches, taxation, anti-money laundering measures, and consumer protection), as well as societal and ethical concerns (environmental impact, privacy, financial inclusion, and potential for illicit use). Drawing on recent empirical studies, case analyses, and theoretical models, the review highlights both the transformative potential of cryptocurrencies to democratize access to financial services and foster innovation, and the significant challengesâsuch as scalability, volatility, regulatory uncertainty, and energy consumptionâthat could inhibit or slow their integration. The paper concludes with a discussion of future research directions, including evolving consensus innovations (e.g. proof-of-stake, sharding), central bank digital currencies (CBDCs), and frameworks for balancing innovation with systemic risk mitigation. KEYWORDS Cryptocurrency, probabilistic forecasting, value-at-risk, expected shortfall, volatility, risk management, threat modeling, fintech, blockchain
Since the introduction of Bitcoin in 2008, the blockchain technology as its underlying architecture, has attracted attention from various sides due to its decentralized and distributed computing characteristics. AS the core advantage of blockchain technology, the consensus mechanism determines various characteristics of blockchain, such as security, scalability, and decentralization. Currently, there are many consensus mechanisms suitable for different scenarios. This paper studies the existing consensus mechanisms from the perspectives of algorithm principles, performance, etc. Firstly, this article divides the existing consensus mechanisms into Proof of Work (PoW), Proof of Stake (PoS), and Byzantine Fault Tolerance (BFT). Secondly, for each type of consensus mechanisms, the study analyzes their algorithmic principles, understands typical solutions and latest ones, clarifies the advantages, disadvantages, and the possible attack methods of various consensus mechanisms. Finally, the paper defines the basic requirements for new consensus mechanisms. It aims to help break through the application bottlenecks of blockchain technology and promote the development of blockchain technology in various scenarios.
This research explores the future synergy between quantum computing (QC) and non-fungible tokens (NFTs) as a tool to revitalize urban transport systems through optimized improvement techniques as well as decentralized governance. Utilizing a conceptual approach combined with thematic analysis, this research provides an integrative framework that combines insights from quantum computing, blockchain governance, and transport geography. Key results include the observation that the integration of these technologies holds the potential to address enduring issues regarding efficiency, sustainability, and equity within transport through exemplary spatial optimization as well as open, participatory governance strategies. However, significant challenges do remain, including energy consumption, the digital divide, as well as regulative uncertainties, requiring careful design, equity-focused protections, as well as effective governance infrastructure. This paper suggests that the actualization of the full potential of these future technologies requires interdisciplinary collaboration as well as a focus on the public good rather than technological advancement alone.
Asheshemi Nelson Oghenekevwe, Okoro Akpohrobaro Daniel, Ayeh Blessing Elohor, Ayo Michael Ifioko ¡ 6 authors
Developments of Web 3.0 technologies present vital problems regarding data confidentiality, authentication of users and their privacy in decentralised systems. The traditional multifactor authentication (MFA) systems have been effective when deployed in Web2 environments but have failed in protecting sensitive information in the decentralised environment because they use centralised servers and are also dependent on static security factors. The paper explores the concept of multifactor authentication that is based on blockchain technology as the effective method of improving the use of data confidentiality in Web3. A blockchain-augmented MFA infrastructure was created on the basis of an Ethereum smart contract, decentralised storage, and biometric data that were cryptographically encrypted. Simulation demonstrated significant increases in security relative to conventional MFA systems, a significant drop in the probability of breaching (0.0270 to 0.0040), an improvement in the entropies, a decrease in the likelihood of session hijacking, and limited mutual information leakage. Also, the blockchain-based system becomes more resistant to Man-in-the-Middle (MITM) and phishing attacks, mitigating them by about 60 per cent and 50 per cent success rates, respectively. Whereas the blockchain MFA made some minor sacrifices in latency and computation cost in the course of authentication, such a trade of costs is productive in the Web3 environment where security and data integrity remain of utmost importance. The study could be useful to developers, security practitioners and policymakers who intend to develop more secure, scalable, and user-centric authentication mechanisms in decentralised apps. As a potential improvement, it is suggested that future research should implement the aspect of consensus optimisation and Layer-2 to increase the efficiency and scalability further.
Financial fraud detection is critical for maintaining the integrity of financial systems, particularly in decentralised environments such as cryptocurrency networks. Although Graph Convolutional Networks (GCNs) are widely used for financial fraud detection, graph Transformer models such as Graph-BERT are gaining prominence due to their Transformer-based architecture, which mitigates issues such as over-smoothing. Graph-BERT is designed for static graphs and primarily evaluated on citation networks with undirected edges. However, financial transaction networks are inherently dynamic, with evolving structures and directed edges representing the flow of money. To address these challenges, we introduce DynBERG, a novel architecture that integrates Graph-BERT with a Gated Recurrent Unit (GRU) layer to capture temporal evolution over multiple time steps. Additionally, we modify the underlying algorithm to support directed edges, making DynBERG well-suited for dynamic financial transaction analysis. We evaluate our model on the Elliptic dataset, which includes Bitcoin transactions, including all transactions during a major cryptocurrency market event, the Dark Market Shutdown. By assessing DynBERG's resilience before and after this event, we analyse its ability to adapt to significant market shifts that impact transaction behaviours. Our model is benchmarked against state-of-the-art dynamic graph classification approaches, such as EvolveGCN and GCN, demonstrating superior performance, outperforming EvolveGCN before the market shutdown and surpassing GCN after the event. Additionally, an ablation study highlights the critical role of incorporating a time-series deep learning component, showcasing the effectiveness of GRU in modelling the temporal dynamics of financial transactions.