Birgit Altrichter, MariaLaura Di Domenico, Glenn Parry, Michael Rogerson
We conceptualize the centralizing-decentralizing paradox of blockchain implementation in supply chains and examine its consequences for complexity. Blockchain’s distributed ledger enables decentralized collaboration by securely sharing data. However, centralizing tendencies for focal firms to seek control over supply chains conflict with this opportunity. Our findings from blockchain for supply chain experts show widespread agreement that using blockchain facilitates decentralized collaboration whilst creating a supply chain systems paradox that often demands high levels of centralization. We find that reducing the paradox to a false dyad for communication masks its underlying complexity. We contribute to theory by developing a novel, nuanced conceptualization of underlying tensions of blockchain in supply chains. We conceptualize paradoxes as complex interacting tensions, advancing understanding of governance in blockchain-based supply chain management.
Samuel A. Oyenuga, Brendan Ubochi, Okechi Onuoha, Nnamdi Nwulu
The rapid growth in IoT applications has brought enormous challenges especially with achieving scalability and security in communicating devices.Traditional centralized security models are inadequate for managing the vast volume of data and diverse communication protocols in IoT environments, making them vulnerable to attacks such as Distributed Denial of Service (DDoS) and unauthorized access.Blockchain technology offers a decentralized alternative with its inherent properties of immutability, transparency, and decentralized consensus, providing a robust security solution for IoT communication.This paper presents a novel blockchain-based framework designed to secure IoT communication by addressing key challenges such as data integrity, privacy, and scalability.The proposed system integrates Ethereum's blockchain, Zero Knowledge (ZK)-Rollups for Layer 2 scaling, and edge computing to optimise both performance and energy efficiency in large-scale IoT networks.The framework achieves a transaction throughput of 2,500 transactions per second with a median latency of 850 milliseconds.ZK-Rollups ensure that 99.8% of transactional data remains off-chain, improving privacy while reducing computational overhead.The system maintains 99.7% uptime during DDoS attacks and reduces energy consumption by 95% compared to traditional Proof of Work (PoW) blockchain systems.These findings indicate that the proposed blockchain-based framework is scalable, energyefficient, and secure, making it a promising solution for large-scale IoT deployments in sectors such as smart cities, industrial automation, and healthcare.
With the rise of modern deep learning, neural networks have become an essential part of virtually every artificial intelligence system, making it difficult even to imagine different models for intelligent behavior. In contrast, nature provides us with many different mechanisms for intelligent behavior, most of which we have yet to replicate. One of such underinvestigated aspects of intelligence is embodiment and the role it plays in intelligent behavior. In this work, we focus on how the simple and fixed behavior of constituent parts of a simulated physical body can result in an emergent behavior that can be classified as cognitive by an outside observer. Specifically, we show how simulated voxels with fixed behaviors can be combined to create a robot such that, when presented with an image of an MNIST digit zero, it moves towards the left; and when it is presented with an image of an MNIST digit one, it moves towards the right. Such robots possess what we refer to as “morphological cognition” – the ability to perform cognitive behavior as a result of morphological processes. To the best of our knowledge, this is the first demonstration of a high-level mental faculty such as image classification performed by a robot without any neural circuitry. We hope that this work serves as a proof-of-concept and fosters further research into different models of intelligence.
Abstract The role of central banks in advancing sustainable (“green”) digital finance is becoming increasingly significant, positioning them as both facilitators and key actors. This chapter begins by examining how climate-related financial risks may require adjustments to the operational frameworks of central bank policy tools, and highlights recent initiatives undertaken by central banks in response. It then reviews specific cases of sustainable digital finance in the central banking context, including: (1) the BIS’s Project Genesis, which integrates the green bond market and carbon markets through digital technologies; and (2) the collaboration between the Bank of Korea (BOK) and the Korea Exchange (KRX) to explore the application of distributed ledger technology and central bank digital currency (CBDC) in carbon trading.
Abstract Emerging digital financial technology has already had a significant impact on financial development and holds significant potential to advance the sustainable finance agenda. Various challenges limit the assessment of environmental risks, as well as the mobilisation of sustainable finance. Digital technology (including artificial intelligence, distributed ledger technologies, cloud computing, the Internet of Things and big data) can help address the risk identification and mobilisation challenges and can at the same time help promote financial inclusion and energy justice. This chapter highlights the potential of digital solutions and presents six proposals to enhance digital technologies to mobilise capital, assess environmental risks and enhance financial inclusion.
As cryptocurrencies began with the launch of Bitcoin in 2009, a technological and financial revolution has created a fundamental menace to worldwide banking infrastructure by its presence. The article is a thorough exposition of the increasing use of cryptocurrencies and its compounding implications to the conventional banking systems. We mention the principles of decentralized finance (DeFi) which explicitly challenge the role between banks, payments, and settlements, lending, and borrowing, and even, the custody of assets. This paper adopts a conceptual and comparative analysis research design to consolidate a number of general layers of scholarly articles, industrial reports and regulation books to develop an overall structure against which to understand this dynamic relationship in a holistic manner. It is analyzed by means of the two-sided impact that semi-protects the traditional bank axiom on one hand, the cryptocurrencies and the DeFi systems are actively disintermediating the traditional banking operations which made delivery of cross-border remittances, P2P lending protocols, and self-custody opportunities faster, cheaper, and more convenient. This is putting competitive pressure on the existing institutions threatening the existence of fee based revenue systems and customer relations. One other, but equally, is that the boarding cryptocurrencies over technological resolutions, namely blockchain and distributed ledger technology (DLT), is borrowed even by the banking sector itself. Banks are learning about DLT to automatize their back-office business, create new digital assets, and the crypto threat establishes their stance through two forms Central Bank Digital Currency (CBDCs) and regulated stablecoins. The implication of this change is evaluated critically depending on the discussion of the potential increase of financial inclusion and financial efficiency in addition to the high level of security risks and the great uncertainty of regulation and the threat of volatility, systemic financial stability. The conclusion of this paper is that crash belongs more to cryptocurrency than to its replacement, and the old banking structures will have to make use of it to be creative, and develop a new value proposal in a more and more decentralized financial system. The future has been defined as requiring a hybrid solution of centralization and decentralization of systems in which they would co exist, compete, and converge.
El Mehdi Badre, SAMIR Kourtite, Slimane Sidouna, M’Hammed Ziane · 5 authors
Motivated by the growing need for secure and efficient cryptographic solutions in blockchain technology, this study explores the cryptographic potential of binary Huff curves defined over the non-local ring <img src=image/13442212_01.gif>, introducing novel group structures for advanced blockchain applications. The research aims to enhance the security and efficiency of cryptographic primitives by leveraging the algebraic properties of these curves, particularly for resource-constrained devices in blockchain ecosystems. We establish a bijection between the Huff curve <img src=image/13442212_02.gif> and the product <img src=image/13442212_03.gif>, enabling an efficient group law that increases the complexity of the discrete logarithm problem (DLP). Methodologically, we define arithmetic operations in <img src=image/13442212_04.gif>, prove the bijection, and derive addition formulas for the curve. These results are applied to adapt the Yak key exchange protocol, enhancing its resistance to DLP-based attacks through the non-local ring's structure. Principal findings demonstrate that <img src=image/13442212_02.gif> achieves approximately <img src=image/13442212_05.gif> group order, doubling the DLP security to <img src=image/13442212_06.gif>-bit compared to <img src=image/13442212_06.gif>/2-bit for standard curves over <img src=image/13442212_07.gif>, with computational efficiency suitable for Internet of Things (IoT) devices. The study contributes to cryptography by proposing a robust framework for blockchain transaction security and secure data management, notably in multi-party computation and zero-knowledge proofs. Key conclusions highlight the curves' potential to secure blockchain validators and IoT nodes, as exemplified in supply chain applications. Novel aspects include the non-local ring's algebraic constraints and the Yak protocol's adaptation for blockchain. Limitations include the need for practical implementation and benchmarking against curves like secp256k1. Practical implications involve improved transaction security and data privacy in blockchain, while social implications include enabling secure, decentralized systems for healthcare and supply chain tracking. Future research should validate performance in real-world blockchain environments and assess resistance to side-channel attacks.
This thesis explores two complementary areas in finance: securities tokenization and interbank payments. First, we propose a tokenization framework extending decentralized finance (DeFi) benefits—accessibility, transparency, efficiency—to real-world securities. While DeFi mechanisms like liquidity pools complicate securities entitlements (e.g., dividends, voting), our solution overcomes this by combining fungible tokens with off-chain accounting and separate smart contracts for entitlements. Implemented on Ethereum, it saves 27% in costs compared to alternatives and supports various securities including stocks and bonds. We also confirm compatibility with liquidity logic in 90% of Ethereum pools. Second, we model Real Time Gross Settlement (RTGS)-based Large Value Payment Systems (LVPS) using queuing theory. RTGS is the most common mechanism for LVPS due to its instant settlement and low risk, but it has high liquidity requirements. Our model yields closed-form solutions for network performance and offers insights into liquidity requirements to aid the design of liquidity saving mechanisms.
With the advancement of edge intelligence technology and the acceleration of urbanization, intelligent transportation systems (ITS) have experienced rapid development. Vehicle-road-cloud (VRC) collaboration was enabled through the coordinated sharing of vehicle-to-vehicle (V2V), vehicle-to-road (V2R), and vehicle-to-cloud (V2C) data in the Internet of vehicles, thereby constructing a more efficient cooperative intelligent transportation system (C-ITS). However, numerous security threats in VRC collaboration were found to severely impede the development of cooperative autonomous driving. The development status of VRC collaboration was first summarized, and the history of autonomous driving and the VRC-based autonomous driving environment were elaborated. Subsequently, attacks and security defense technologies in VRC collaboration were systematically categorized into two types: classical information security mechanisms and defense technologies, which were detailed from five aspects—information availability, integrity, confidentiality, authenticity, and non-repudiation; and machine learning-based security threats and defense technologies, which were analyzed from both centralized and distributed perspectives. Finally, future development directions and research priorities of VRC collaborative security technologies were forecasted, primarily covering federated learning, blockchain technology, secure multi-party computation, zero-knowledge proof, and differential privacy technology.
This paper presents a novel health data analysis platform for improved individualized risk forecasting of permanent pacemaker implantation (PPI) following transcatheter aortic valve replacement (TAVR) procedures. Specifically, we introduce XGBoost-federated adaptive interpolation transfer learning (XG-FedAIT)—a platform that integrates heterogeneous hospital data sets via adaptive output-level interpolation and performance-weighted model ensembling. This approach facilitates federated learning across institutions with different feature spaces and prediction targets, such as time-to-event and binary models, eliminating structural and semantic mismatches prevalent in regular federated transfer learning. To ensure secure, privacy-preserving, and general data protection regulation (GDPR)-compliant data exchange, we propose a dual-chain blockchain architecture integrating proof of authority (PoA), zero-knowledge proofs (ZKPs), and chain-specific smart contracts, and off-chain encrypted storage through Filecoin. Experimental evaluation proves that the PrimaryChain handles over 300 tx/s with a median latency of 500 ms, and the SecondaryChain offers 99.8% data availability and decentralized access control. The system is scalable to handle up to 2,500 transactions/hour, and the federated learning pipeline classifies PPI risk with an F1-score of 0.85 and AUROC of 0.91. These results support the effectiveness of our system in delivering real-time, regulation-compliant, and clinically actionable cardiac care in distributed environments.
Open access
Artificial Intelligence in Healthcare and Education
Inna Kovalchuk, Victoria Melnyk, Tamara Novak, Anna Pakhomova · 5 authors
The article examines innovative approaches to state support for agribusiness through the implementation of virtual asset technologies in the Ukrainian legal field, taking into account international experience. The relevance of the topic is due to the need to modernize the existing mechanisms for financing the agricultural sector in the context of the digital transformation of the economy and the development of the global crypto-asset market. The authors analyzed the current state of legal regulation of virtual assets in Ukraine, in particular in the context of the Law of Ukraine "On Virtual Assets" and its implementation. Also, it was outlined the main problems and obstacles to the introduction of innovative financial instruments in the agricultural sector including: instability of the regulatory framework, insufficient integration of digital solutions into state support programs, as well as low technological readiness of small and medium-sized agricultural producers. The authors studied the international experience of using blockchain technologies to support the agricultural sector in countries such as the USA, Australia, Singapore and the countries of the European Union. In particular, the authors paid attention to the analysis of legal models of tokenization of agricultural assets and the use of smart contracts to optimize the processes of state subsidies. Based on the analysis, the authors proposed a comprehensive model of integration of virtual asset technologies into the mechanisms of state support for agribusiness in Ukraine. The key elements of this model are: the creation of special legal regimes for agricultural tokens and NFTs, the formation of infrastructure for the digital interaction of farmers with state institutions, the implementation of blockchain solutions for the transparent distribution of subsidies, as well as the development of a legal framework for agricultural digital cooperatives. The authors substantiated the need to amend the legislation of Ukraine, in particular the Law of Ukraine "On State Support of Agriculture of Ukraine", the Tax Code and relevant regulations on virtual assets. Also, the authors identified the potential risks and advantages of the proposed innovations for both agricultural producers and the state. The results of the research are of theoretical and practical importance for the formation of state policy in the field of the agro-industrial complex of Ukraine, taking into account the global trends in digitalization and the use of distributed ledger technologies to ensure the efficiency, transparency and accessibility of state support for agribusiness. Keywords: virtual assets, blockchain, smart contracts, state support for agriculture, tokenization of agricultural assets, agricultural sector, digital transformation.
Jeongin Lee, Geunyeong Choi, Jihyo Han, Jungheum Park
Monero, a privacy-preserving cryptocurrency, employs advanced cryptographic techniques to obfuscate transaction participants and amounts, thereby achieving strong untraceability. However, digital forensic approach can still reveal sensitive information by examining off-chain artifacts such as memory and wallet files. In this work, we conduct an in-depth forensic analysis of Monero's wallet application, focusing on the handling of public and private keys and the wallet's data storage formats. We reveal how these keys are managed in memory and develop a memory scanning algorithm capable of identifying key-related data structures. Furthermore, we analyze the wallet keys and cache files, presenting a method for decrypting and interpreting serialized keys and transaction data encrypted with a user-specified passphrase. Our approach is implemented as an open-source Volatility3 plugin and a set of decryption scripts. Finally, we discuss the applicability of our methodology to multi-cryptocurrency wallets that incorporate Monero components, thereby validating the generalizability of our techniques.
This thesis explores how decentralization shaped the organization and function of public health systems in Canada through the comparison of Alberta and Ontario. Decentralization has been widely promoted as a way to increase responsiveness and local engagement in health systems broadly, while centralization is often seen as a means to improve coordination and efficiency. Several Canadian provinces have been pursuing centralization reforms in their health systems and the variation in public health systems across the provinces provides an opportunity for comparative analysis and learning. A comparative case study design was employed, focusing on Edmonton Zone (Alberta Health Services) and Ottawa Public Health as representative local public health units functioning in one system characterized as centralized (Alberta) and one as decentralized (Ontario). The Decision Space Analysis was used as an analytical framework to assess decentralization in both cases across key health system functions from 2011 to 2023. The opioid-related crisis served as a tracer for this study, adding another layer of focus to the data collection and analysis to explore how decentralization as a structure is related to public health responses. Data collection involved 41 documents and 10 key informant interviews for the Alberta case, and 45 documents and 9 key informants for the Ontario case. Content and thematic analysis techniques were used to conduct the Decision Space Analysis across health system domains such as financing, service organization, human resources and governance, and inductive analysis techniques were used to better understand how decentralization was experienced in general and for the tracer. Ottawa Public Health generally exhibited wider decision space than Edmonton Zone and differences emerged in areas of human resources and governance. However, the two local public health units also demonstrated similarities and overlap in areas of finance and service organization. Despite structural differences, both jurisdictions saw the implementation of comparable responses to the opioid-related crisis with some differences in approaches to safer supply programs. The potential reasons for these similarities and differences are explored. This study contributes to public health systems and services research by advancing a more nuanced and function-specific understanding of the structural arrangements in Alberta and Ontario’s public health systems, moving beyond simplistic dichotomies of centralization and decentralization. The utility of the Decision Space Analysis, both as an analytical framework and a way to understand policy debates, is also discussed.
This study investigates the specific factors affecting blockchain or the usage intention of distributed ledger technology (DLT), specifically availability, diversity, and economic value, from the perspective of a unified theory of technology acceptance. Users of DLT in public and private sectors were surveyed. Using a structural equation model, the results indicate that availability and economic value affect performance expectancy, while availability, diversity, and economic value have an influence on effort expectancy. Performance expectancy and transparency have a positive effect on the intention to use DLT, which in turn exerts a positive effect on usage behavior. This study provides implications for researchers in that it attempts to investigate the factors directly (like performance expectancy and transparency) or indirectly (like availability and economic value) affecting the usage intention of DLT based on the extended unified theory of acceptance and encompassing diverse industries that adopt DLT, such as the public, IT, financial, service medical, and logistics sectors.
This policy paper reviews the evolution of research from 2016 to 2024 on the role of digital assets in illicit financial flows and evaluates the effectiveness of existing detection and prevention strategies. It highlights two central policy imperatives for Latin America: (i) fostering regional cooperation among central banks to harmonize anti-money-laundering standards and address regulatory arbitrage, and (ii) integrating supervisory technologies (SupTech and RegTech) into compliance frameworks to improve detection capacity. The paper concludes that combining technological innovation with coordinated regional regulation is essential to safeguard financial integrity in the digital-asset era.
The study aims to examine how blockchain is used in the multimodal and interdisciplinary metaverse as a nexus of education and training, accounting, banking and finance, entertainment and media, marketing and e-commerce, and retail, healthcare, and wellness. It seeks to evaluate the influence of blockchain combined with artificial intelligence, the Internet of Things, and other emerging technologies in the metaverse, so evaluating the challenges and concerns in the field, new business prospects, and sustainable development paths corresponding to Sustainable Development Goals. Using a Systematic Literature Review (SLR) technique, this article addresses the problem from a commercial viewpoint. The study investigates the topic structure of the literature by means of Biblioshiny for R combined with VOSviewer version 1.6.20. Furthermore, increasing the analytical depth is a bibliographic coupling method used on a dataset of 172 Scopus (2024) items. The study underlines the economic rationality and direct consequences of the characteristics of the blockchain—NFTs, DeFi, cryptocurrencies, transparency, decentralization, and security—on the relevance of business models in the metaverse. The information provided here is a vital literature study on how the blockchain addresses issues in constructing and metamorphosing the metaverse from several sectors and angles. In the framework of the metaverse, this article offers a thorough theoretical study of the possibilities and possible challenges in blockchain integration.
Jinfa Hong, Bohao Zhang, Gaoyu Mao, Patrick S. Y. Hung · 5 authors
Lattice-based cryptography (LBC) is an essential direction in the fields of homomorphic encryption (HE), zero-knowledge proofs (ZK), and post-quantum cryptography (PQC), while number theoretic transformations (NTT) are a performance bottleneck that affects the promotion and deployment of LBC applications. Field-programmable gate arrays (FPGAs) are an ideal platform for accelerating NTT due to their reconfigurability and parallel capabilities. High-level synthesis (HLS) can shorten the FPGA development cycle, but for algorithms such as NTT, the synthesizer struggles to handle the inherent memory dependencies, often resulting in suboptimal synthesis outcomes for direct designs. This paper proposes a systematic HLS co-design to progressively guide the synthesis of NTT accelerators. The approach integrates several key techniques: arithmetic module resource optimization, conflict-free butterfly scheduling, memory partitioning, and template-based automated design fusion. It reveals how to resolve pipeline bottlenecks in HLS-based designs and expand parallel processing, guiding microarchitecture iterations to achieve an efficient design space. Compared to existing HLS-based designs, the area-latency product achieves a performance improvement of 1.93 to 191 times, and compared to existing HDL-based designs, the area-cycle product achieves a performance improvement of 1.7 to 10.6 times.
Existing regulatory frameworks for decentralized anonymous payments help combat illicit activities such as money laundering and terrorism financing. However, With the development of the European Union's General Data Protection Regulation (GDPR) and data sovereignty, Existing frameworks struggle to balance privacy with regulatory compliance, often compromising user autonomy and data sovereignty. To address this, we propose the Linkable Distributed Regulatory Tag (LDRT) scheme, which enables traceability without altering transaction structure by leveraging Paillier homomorphic encryption and secret sharing. Building upon this, we introduce Decentralized Anonymous Payment with Data Sovereignty(DAPDS), the first regulatory framework for decentralized anonymous payments that complies with data sovereignty. DAPDS supports both UTXO and account-based models and employs a distributed regulator group with incentives to prevent dishonest behavior. We define and analyze the security properties of both LDRT and DAPDS, proving anonymity, linkability, traceability, collusion resistance, data sovereignty, distributed regulation, and fairness of incentive mechanism. Our work provides a valuable reference for future regulatory framework paradigms for anonymous privacy-preserving traceable blockchain. Experimental results show that DAPDS only incurs an additional 34ms of time cost over ETH in transacation phase and an average of only 2.66s per tracing request in tracing phase.
Yield of tomatoes ( Solanum lycopersicum ) grown in high tunnels in Wanatah, IN, USA, was evaluated using two plant support systems: stake-and-weave or vertical-string. With stake-and-weave, plants were not pruned; stakes were placed every two plants and string was woven horizontally along either side of the plants along the row. With vertical-string, indeterminate cultivars Big Beef and Cherokee Purple were pruned to two stems and each stem was clipped to a vertical string. For the determinate cultivar Mountain Fresh, all branches below the first main stem flower cluster except one were removed and the main stem and major branches were clipped to vertical strings. Yield of US Department of Agriculture (USDA) no. 1 and no. 2 fruit was significantly higher for all cultivars with stake-and-weave than with vertical-string: Big Beef averaged 20.6 and 8.7 lb/plant, Cherokee Purple averaged 8.7 and 2.4 lb/plant, and Mountain Fresh averaged 20.1 and 16.9 lb/plant for stake-and-weave and vertical-string, respectively. The percentage of yield that was culled was less with stake-and-weave than with vertical-string for cultivars Big Beef and Cherokee Purple, but not for Mountain Fresh. Yield of USDA no. 1 and no. 2 fruit over the first 3 weeks of harvest was higher for stake-and-weave by 20% for cultivar Big Beef, and it showed no significant difference for cultivars Cherokee Purple or Mountain Fresh. In this system, when tomatoes were harvested for a period of 8 to 10 weeks, the stake-and-weave system produced more marketable yield than pruning to two or several stems and clipping each stem to a vertical string.
Eduardo Andrés Calderón Marenco, Romina Mariela Sánchez Silveyra, Juan Manuel Rodrigo, Gabriel Ravelo-Franco
El artículo analiza el efecto de la inteligencia artificial en la contratación inteligente y la protección de datos personales y argumenta que la automatización mediante smart contracts plantea desafíos regulatorios, ante la falta de un marco normativo adecuado para garantizar la privacidad y la seguridad jurídica en Latinoamérica. A través de un análisis comparado de los marcos normativos de Argentina, Perú, Colombia, Ecuador y la Unión Europea, se identifican avances y vacíos en la regulación de estas tecnologías, y se destaca que, aunque algunos países han reconocido la validez jurídica de los contratos inteligentes, la protección de los datos almacenados en blockchains sigue siendo un reto. Asimismo, se aborda el concepto de lex criptográfica como un sistema de autorregulación basado en la descentralización tecnológica, lo que genera tensiones con principios tradicionales del derecho. El artículo concluye que la creciente automatización contractual exige una actualización normativa que armonice la eficiencia tecnológica con la protección de los derechos fundamentales, y propone el desarrollo de un marco regulador que garantice la seguridad jurídica, la transparencia en el tratamiento de datos y la responsabilidad en la toma de decisiones automatizadas, conforme a los estándares internacionales y europeos de protección de datos.
Moderne Blockchains verarbeiten mittlerweile Zehntausende Transaktionen pro Sekunde. Mit steigendem Durchsatz wachsen jedoch auch die Anforderungen für die Verifikation von Blockchains. Zentralisierte Node-as-a-Service (NaaS)-Anbieter (z.B. Infura oder Alchemy) bieten zwar praktische APIs, schaffen jedoch zusätzliche Vertrauensabhängigkeiten und bergen Risiken in Bezug auf Datenschutz und Zensurfreiheit. Ein selbst betriebener Full Node ermöglicht Datenzugang ohne zusätzliche Vertrauensannahmen, ist für die meisten Nutzerinnen und Nutzer jedoch aufgrund des hohen Ressourcenbedarfs kaum praktikabel. Im Gegensatz dazu arbeiten Light Clients deutlich ressourcenschonender, können dafür den vollständigen Anwendungszustand nicht rekonstruieren. Ein neuer Ansatz, der als Sparse Client (bzw. Partially Stateless Client) bekannt ist, ermöglicht dagegen die verifizierbare Überwachung eines Teilzustands der Blockchain, indem ausschließlich jene Transaktionen heruntergeladen, ausgeführt und gespeichert werden, die diesen Teilzustand lesen oder verändern. Bisher fehlt eine fundierte wissenschaftliche Aufarbeitung: Die einzige verfügbare Arbeit zu diesem Thema weist deutliche Limitierungen auf und wurde weder implementiert noch umfassend evaluiert. In dieser Arbeit präsentieren wir zwei Sparse-Client-Protokolle für EVM-kompatible Blockchains: Sparseth für zustandsbasierte Synchronisation und Eventeth für ereignis-basierte Synchronisation. Beide Protokolle ermöglichen es Nutzerinnen und Nutzern, überprüfbare Teilmengen der globalen Transaktions- oder Ereignissequenz und des damit verbundenen Zustands zu verwalten, ohne dass zusätzlicher Validator-Aufwand erforderlich ist. Sparseth nutzt einen Interaktionszähler, um sicherzustellen, dass keine relevanten Transaktionen ausgelassen werden, während Eventeth eine kryptographische Hash-Kette einsetzt, um die Integrität und Vollständigkeit der Ereignisse zu gewährleisten. Im Gegensatz zu bestehenden Ansätzen arbeiten beide Protokolle vollständig auf der Ausführungsschicht und sind mit EVM-basierten Blockchains kompatibel. Unsere formale Analyse zeigt, dass beide Protokolle im angenommenen Widersacher-Modell Sicherheit, Liveness und spärliche Gültigkeit garantieren. Unsere Implementierung in Go demonstriert die praktische Umsetzbarkeit: Event Nodes senken den Bandbreitenbedarf um über 95%, Sparse Nodes reduzieren die auszuführenden Transaktionen um 92% gegenüber Full Nodes. Die Gas-Kosten steigen um 4-16% für typische dApp-Transaktionen, ein Mehraufwand, der sich durch L2-Lösungen und ökonomische Anreize weiter mindern lässt.
Rajasekaran P, M. Duraipandian, Johny Renoald Albert
The increasing rate of growth of the Internet of Things (IoT) in cloud-hospitality health has brought in data storage, transmission, and security challenges with the advent of quantum-enabled threats. Traditional compression methods struggle with computational inefficiency and the threat of invasion of privacy. This paper proposes a Quantum-Enhanced Zero-Knowledge Healthcare Compression Network for solving these challenges by combining Zero-Knowledge Proofs and Quantum-Inspired Deep Learning. The main goal is to provide privacy-preserving, efficient data compression along with optimizing computation costs and safeguarding sensitive healthcare records. Drawbacks in present cryptographic techniques, e.g., high computational costs in homomorphic encryption and scalability limitations in blockchain, require a novelty Adaptive Quantum-Assisted Zero-Knowledge Verification and Quantum Fusion-AutoCNN Encoder (QF-AutoCNN) to overcome this research. This work’s originality lies in combining Quantum zk-SNARKs, Hybrid Quantum Feature Encoding, and Reinforcement Learning-Based Challenge Optimization to provide better security, compression ratio, and verification efficiency. Experimental results show better accuracy (0.9816), improved F-measure (0.9709), and less computational overhead, better than other current methods such as convolutional neural networks-encryption and proxy re-encryption. This research greatly adds to safe cloud healthcare IoT by lessening privacy threats, maximizing storage space, and minimizing processing time, guaranteeing real-time handling of medical information.
The shift from fossil-based energy systems to renewable sources like solar, wind, and hydro presents both opportunities and challenges for developing countries aiming to expand energy access, promote economic growth, and meet climate goals. This study examines the technological, financial, institutional, and governance aspects of clean energy transitions, focusing on regional disparities and implications for low- and middle-income economies. A systematic review of literature was carried out using the SPAR-4-SLR methodology across Scopus, Web of Science, and Google Scholar. Only peer-reviewed studies published in English from 2009 to 2025 were included, guided by four research questions: (1) technological and resource endowments, (2) capital structuring and financial market dynamics, (3) institutional and policy frameworks, and (4) decentralized, digital energy governance. Search terms were tailored for each theme, and studies were classified by topic, region, and methodology. Results show that decentralized renewable systems—especially solar micro-grids—offer affordable alternatives to fossil fuels in rural and off-grid areas, enhancing job creation, energy security, and poverty reduction. Examples from Kenya, India, and Southeast Asia highlight the importance of policy consistency, financial innovation, and institutional preparedness in promoting clean energy deployment. Still, ongoing challenges such as high initial costs, infrastructure gaps, and limited technical skills continue to hinder progress in many regions. • Institutional and financial factors outweigh resource availability in clean energy. • Local policy tools often outperform broad international frameworks of clean energy. • Blended finance reduces cost barriers in early-stage clean energy projects. • Inclusive planning links clean energy to health and equity gains. • Technology transfer works best with local training and governance support.