Shiji Mol F R, J. Ayyana Prabu, R. Santhana Krishnan, S. Jeeva Paulin · 6 authors
Ensuring vaccine integrity requires rigorous cold-chain management, as even minor temperature deviations can compromise safety, cause financial losses, and endanger public health. Conventional monitoring systems, dependent on centralized databases and manual oversight, remain prone to delays, inaccuracies, and tampering. To address these limitations, we propose an integrated framework that combines deep learning and blockchain for secure, predictive, and real-time cold-chain monitoring. A distributed network of IoT sensors captures temperature, humidity, vibration, and GPS data at one-minute intervals. Long Short-Term Memory (LSTM) networks forecast short-term temperature trends, Autoencoders (AE) detect anomalies, and one-dimensional Convolutional Neural Networks (1D CNN) classify shipment states as Safe, At Risk, or Spoiled. A decision engine fuses outputs from these models into a unified risk score, enabling timely and data-driven interventions. Critical events and metadata are immutably recorded on the Ethereum blockchain, while raw sensor data is stored off-chain using IPFS to ensure auditability and efficiency. The system also supports automated alerts, real-time monitoring through Grafana dashboards, and adaptive model retraining for continuous improvement. Evaluation covers forecasting accuracy, anomaly detection precision, classification performance, and blockchain efficiency. By uniting predictive analytics with tamper-proof logging, the proposed framework reduces vaccine spoilage, strengthens supply chain resilience, and offers a scalable solution for broader temperature-sensitive logistics applications.
Because of the rapid acceleration of cloud computing, data transfer security and intrusion detection in cloud networks have become emerging areas of concern. All traditional security mechanisms have central vulnerabilities, cannot detect real-time threats, and are ineffective against zero-day attacks. Signature-based approaches of existing intrusion detection systems (IDS) do not cover the dynamically changing nature of cyber threats. Conventional blockchain security methods suffer from poor scalability and dynamic threat analysis. Therefore, this research proposes integrating Ethereum Blockchain and Deep Learning to construct a well-founded security framework for cloud networks with data migration security and real-time intrusion detection. The architecture has five distinct methods, each of which deals with particular security issues. Blockchain-Aware Federated Learning for Secure Model Training (BAFL SMT) guarantees tamper-proof and decentralized deep learning model training, which reduces model poisoning attacks by 98.4%. Graph Neural Networks for Adaptive Intrusion Detection (GNN-AID) captures graph structures for real-time anomaly detection in networks while reducing false positives to 1.2%. Quantum-inspired Variational Autoencoders (QI VAE ZDAD) provide enhanced zero-day attack detection, with an improved detection rate of 92%. Self-Supervised Contrastive Learning for Blockchain Security Auditing (SSCL-BSA) detects smart contract vulnerabilities automatically, resulting in an 87% reduction in fraud risk. Finally, Hierarchical Transformers for Secure Data Migration (HT SDM) enhance the transfer security of large-scale cloud data, achieving an attack classification accuracy of 99.1%. Overall, this multi-layer security framework will greatly enhance cloud security by preserving data integrity, cutting down the intrusion detection time by up to 65%, and enhancing response mechanisms. By marrying the immutable transparency of blockchain with superior anomaly detection at deep learning, this research provides a scalable, real-time, and intelligent approach to strengthening security against the backed-up transfer of data within cloud networks.
The rapid development of decentralized technologies and blockchain is transforming the methods of authentication, data management and the implementation of digital human rights, which actualizes the need to form a new identity paradigm based on user autonomy and trustful interaction without intermediaries. The purpose of this article is to substantiate self-sovereign identity as the foundation of trust and digital asset management within the Web3 ecosystem. The research methodology combines comparative legal and formal-dogmatic analysis, structural-functional modeling of the three-way interaction among issuer, holder, and verifier, as well as a problem-oriented review of the technical standards and practices of early platforms (Sovrin, uPort). It is demonstrated that the emergence of self-sovereign identity is a natural response to the shortcomings of centralized and federated identification models in Web 2.0 (OAuth 2.0, OpenID Connect): dependence on providers, concentration of leakage risks, and inability to disclose attributes selectively. The article reveals the mechanism of trust formation in the self-sovereign identity system, which is based on a three-party model of interaction between the issuer, the holder and the verifier; in this model, data authenticity is ensured using cryptographic verifiability through decentralized identifiers and verifiable credentials, which allows minimizing the participation of intermediaries, reducing the surface of possible attacks and guaranteeing the autonomy of the data subject in the process of managing their own digital identity. The key principles of self-sovereign identity (control, availability, transparency, minimization of disclosure, portability, security/resilience, and consent) are systematized, and their applied role in forming a «trust architecture» in Web3 (DAO, DeFi, NFT) is demonstrated. The study revealed a regulatory asymmetry between the technological development of self-sovereign identity systems and the level of their legal regulation. For Ukraine, key regulatory gaps have been specified that hinder the implementation of self-sovereign identity systems and limit the possibility of integrating Ukrainian e-government systems into the international Web3 space: the legislation lacks definitions of the terms «self-sovereign identity» and «decentralized identifier», which is why these concepts have no legal status in Ukraine; the current legal framework for electronic identification and personal data protection is incompatible with the principles of decentralization, self-control, and minimization of information disclosure, which underlie the SSI model. The practical significance of the results lies in the proposed holistic legal and technical framework for developing Web3 trust services, which enables the design of interoperable and secure processes for managing digital assets, prioritizing personal sovereignty over data.
Artur Iasenovets, Fei Tang, Huihui Zhu, Ping Wang · 5 authors
Permissioned blockchains ensure integrity and auditability of shared data but expose query parameters to peers during read operations, creating privacy risks for organizations querying sensitive records. This paper proposes a Private Information Retrieval (PIR) mechanism to enable private reads from Hyperledger Fabric's world state, allowing endorsing peers to process encrypted queries without learning which record is accessed. We implement and benchmark a PIR-enabled chaincode that performs ciphertext-plaintext (ct-pt) homomorphic multiplication directly within evaluate transactions, preserving Fabric's endorsement and audit semantics. The prototype achieves an average end-to-end latency of 113 ms and a peer-side execution time below 42 ms, with approximately 2 MB of peer network traffic per private read in development mode--reducible by half under in-process deployment. Storage profiling across three channel configurations shows near-linear growth: block size increases from 77 kilobytes to 294 kilobytes and world-state from 112 kilobytes to 332 kilobytes as the ring dimension scales from 8,192 to 32,768 coefficients. Parameter analysis further indicates that ring size and record length jointly constrain packing capacity, supporting up to 512 records of 64 bytes each under the largest configuration. These results confirm the practicality of PIR-based private reads in Fabric for smaller, sensitive datasets and highlight future directions to optimize performance and scalability.
The potential of agricultural data (AgData) to drive efficiency and sustainability is stifled by the "AgData Paradox": a pervasive lack of trust and interoperability that locks data in silos, despite its recognized value. This paper introduces AgriTrust, a federated semantic governance framework designed to resolve this paradox. AgriTrust integrates a multi-stakeholder governance model, built on pillars of Data Sovereignty, Transparent Data Contracts, Equitable Value Sharing, and Regulatory Compliance, with a semantic digital layer. This layer is realized through the AgriTrust Core Ontology, a formal OWL ontology that provides a shared vocabulary for tokenization, traceability, and certification, enabling true semantic interoperability across independent platforms. A key innovation is a blockchain-agnostic, multi-provider architecture that prevents vendor lock-in. The framework's viability is demonstrated through case studies across three critical Brazilian supply chains: coffee (for EUDR compliance), soy (for mass balance), and beef (for animal tracking). The results show that AgriTrust successfully enables verifiable provenance, automates compliance, and creates new revenue streams for data producers, thereby transforming data sharing from a trust-based dilemma into a governed, automated operation. This work provides a foundational blueprint for a more transparent, efficient, and equitable agricultural data economy.
Advanced blockchain technologies and growing environmental and economic uncertainties have Motivated us to investigate the impact of climate policy uncertainty (CPU) and global economic policy uncertainty (GEPU) on five green cryptocurrenciesâADA, EOS, IOTA, XLM, XTZâselected based on energy efficiency and mining processes. We examined the short- and long-run impacts of alternative assets on these cryptocurrencies using a nonlinear autoregressive distributed lag model. In the long run, these cryptocurrencies are negatively affected by CPU and GEPU, questioning their safe-haven potential. In the short run, ADA, EOS, and XLM share a positive asymmetric relationship with CPU, whereas all cryptocurrencies have a negative asymmetric relationship with GEPU. Therefore, they can be considered a safe haven. In the short and long term, green bonds exert a positive impact, whereas interest rates, the S&P 500, and the gold index negatively impact these cryptocurrencies. In the short run, Bitcoin shows a negative relationship with EOS, IOTA, and XTZ and a positive relationship with ADA and XLM. Over the long term, Bitcoin exhibits a positive correlation with all cryptocurrencies. USD exhibits a positive relationship in the short run and a negative relationship in the long run with all cryptocurrencies. The findings offer practical implications for portfolio construction and investors dealing in the green cryptocurrency market.
In complex environments such as those incorporating distributed and edge computing, middleware plays a critical role in meeting the communication and performance requirements of distributed systems by providing communication flow and integration capabilities. Its inherent advantages, such as abstraction of complexities, enhanced interoperability and scalability, make it ideal for managing tasks such as federated learning in edge AI environments. In addition, by supporting secure and energy-efficient operations, the middleware fosters sustainability, enabling green blockchain solutions and low-power distributed ledger technologies (DLTs) to thrive for managing dynamic ecosystems such as dAIEDGE. This deliverable D5.3, "Middleware prototype" presents the first version of dAIEDGE middleware. This work has been developed during the first year of dAIEDGE project from M4 to M16. In general, the document outlines the first version of the middleware developed collaboratively with task partners, by the University of Salamanca (USAL) as part of Task T5.2, "Middleware and Networks for Edge AI," within the dAIEDGE project. This task reflects a joint effort involving multiple participants, including BCA, BTH, CETIC, KUL, VICOM, and UEDIN.
Abstract This research paper provides a comprehensive analysis of Bitcoin, the worldâs preeminent cryptocurrency, focusing on the economic drivers of its price formation, its broader impact on the economy, and the evolving dynamics of its volatility. Drawing on high-frequency econometric modeling, time-series analysis, and network-based prediction methods, the paper synthesizes insights from leading empirical studies to elucidate the factors shaping Bitcoinâs price, including supply-demand fundamentals, investor behavior, macro-financial indicators, transaction network structure, and the influence of derivative markets. Additionally, it explores Bitcoinâs adoption in key industries, its intrinsic and extrinsic value determinants, and the implications of its volatility for financial stability. The study concludes by reflecting on the future trajectory of Bitcoin as it transitions from speculative asset to potential mainstream medium of exchange, considering regulatory, technological, and market challenges. Keywords: Bitcoin, cryptocurrency, price formation, volatility, supply-demand, GARCH, partial differential equations, transaction networks, futures markets, economic impact
ABSTRACT The Water Reserve Unit (WRU) proposes a new category of securitized, resource-backed reserve assets that integrate verified freshwater reserves into the global financial architecture.Unlike speculative digital assets, WRU represents a regulated and institutionally verified instrument designed to enhance global financial stability through linkage to real, measurable resources. The framework unites economic, legal, and technological dimensions â including distributed-ledger verification, sustainable-development principles, and international governance mechanisms â to enable transparent, compliant, and auditable issuance of water-backed value units.Technological transparency is achieved through distributed-ledger proof-of-reserve mechanisms ensuring real-time verification, accountability, and cross-border interoperability. Legally, the concept builds upon the United Nations General Assembly Resolution 64/292 (2010), which recognizes the human right to safe and clean drinking water and sanitation, and aligns with the UN Sustainable Development Goal 6 (Clean Water and Sanitation), embedding this right within a financial-institutional framework. By translating normative principles of international water law â such as those articulated in the 1997 UN Convention on the Law of the Non-Navigational Uses of International Watercourses â into measurable reserve instruments, WRU operationalizes the linkage between resource security and financial stability. Methodologically, the WRU framework is grounded in institutional economics (Commons, North), ecological macroeconomics, and sustainability finance, integrating valuation of natural capital with modern digital auditability. It provides a conceptual and technological foundation for recognizing water as a reserve-eligible asset, comparable in function to gold or Special Drawing Rights (SDRs), yet intrinsically tied to the planetâs most vital resource. Thus, WRU is not a cryptocurrency or utility token but a sovereignly regulated, resource-anchored financial standard â a new class of sustainability-linked reserve assets that integrate environmental resilience, economic equity, and technological trust within the evolving global financial system.
Public procurement in Africa is hindered by systemic corruption, inefficiency, and a lack of accountability, undermining economic growth and public trust. This analysis examines the transformative potential of smart contracts, built on Distributed Ledger Technology (DLT), as an innovative solution to enhance transparency and integrity in the continent's procurement systems. The study analyzes how smart contracts, by embedding procurement rules into immutable code, minimize human discretion and create tamper-proof audit trails for processes from bid submission to payment. Drawing on global precedents and emerging African cases (including DLT use in Guinea-Bissau's public wage bill), the paper finds that while smart contracts are technically feasible and highly beneficial, their successful adoption is contingent upon overcoming significant structural barriers. These challenges include adapting outdated legal frameworks to recognize the legal personality of contract code, addressing low digital infrastructure compatibility, and managing cultural resistance from officials who benefit from the existing discretionary systems. The paper concludes with key recommendations for African governments, emphasizing the necessity of parallel legal reform, targeted capacity building, and strong political commitment to leverage this technology for achieving Sustainable Development Goal 16 (Peace, Justice, and Strong Institutions).
This article analyzes the impact of global financial technologiesâspecifically Blockchain, decentralized finance systems (DeFi), and Central Bank Digital Currencies (CBDC)âon the banking system within the IMRAD framework. The paper examines the transformational influence of modern FinTech innovations on traditional banking services, their role in expanding financial inclusion, and the associated issues of security and regulatory challenges. The study also highlights the prospects of implementing such technologies in developing countries like Uzbekistan.
Ăder Johnson de Area LeĂŁo Pereira, Thanmillys Nadhynne de Lima da Conceição, Emanuel Cruz Lima
The urgent need to mitigate climate change has elevated green hydrogen as a sustainable alternative to fossil fuels, while green cryptocurrencies have emerged to address the environmental concerns of traditional cryptocurrency mining. This study investigates the dynamic correlation between the green hydrogen market and selected green cryptocurrencies (Cardano, Stellar, Hedera, Algorand, and Chia) from July 2021 to April 2024, utilizing the Dynamic Conditional Correlation GARCH (DCC-GARCH) model with robustness checks using EGARCH and GJR-GARCH specifications. Our findings reveal significant correlations, with peaks reaching up to 50% in 2022, a period likely influenced by the Russia-Ukraine conflict. Subsequently, a decline in these correlations was observed in 2023. These results underscore the interconnectedness of sustainability-driven markets, suggesting potential contagion effects during periods of global instability. The high persistence of correlation shocks (α + ÎČ values approaching unity) indicates that correlation regimes tend to be long- lasting, with important implications for portfolio diversification and risk management strategies. Robustness checks using EGARCH and GJR-GARCH specifications confirmed qualitatively similar patterns, reinforcing the validity of our findings into the evolving landscape of green finance and energy.
This study adds a new dimension to the body of research by analyzing the impact of fiscal decentralization (FD) on ecological footprints (EF) in Pakistan. In Pakistan, the author examined how financing dependency (FD) affects economic efficiency (EE) from 1990 to 2022, considering time series data with the variables of renewable energy consumption (REC), nonrenewable energy consumption (NREC), GDP and trade openness (TOP). Based on the obtained data, the Auto Regressive Distributed Lag (ARDL) model is chosen. To promote environmental sustainability, the regression analysis reveals that NREC, GDP, and TOP improve EF in Pakistan, while FD and REC reduce EF. This study suggests that Pakistan should optimize the integration of strategies that improve ecological quality by providing the lower level of government with access to environmentally aware technological advancements. These findings could be considered as a policy recommendation.
The clean energy (CE) industry is rapidly expanding due to improvements in technology, policy objectives, and global interest in sustainable financing. This chapter presents important technological improvementsâincluding energy storage systems, smart grid networks, hydrogen as an energy carrier, and newer renewable sourcesâwhich have enhanced the efficiency, reliability, and attractiveness of CE investments. However, the outlook for the CE sector is robust, where the International Energy Agency predicts that by 2025 renewables will lead all net capacity additions across the globe. Furthermore, the expansion of decentralized energy systems and green finance, like green bonds, is set to provide different investment opportunities. Still, some strategic recommendations for investors include developing technological and geographical diversification, having a long-term view, being aware of policy changes, and including environmental, social, and governance (ESG) factors in their investment decisions to achieve sustainability objectives. Investments in CE have economic rewards, but the investments are also good for core social issues of global context in areas like clean energy, combating climate change, and innovative sustainability solutions. Toward the end of the chapter, it is suggested that to sustain continued growth within the CE sector, there has to be a continuous emphasis on technological advancement and active supportive policies, international collaboration, and a focus on inclusivity and resilience in CE initiatives.
This chapter offers historical, contemporary, and future insights into the workings of the evolving global music industry. Scott Cohen, a seasoned entrepreneur and major-label strategist, shares firsthand perspectives on the challenges that labels encounter, how technology has consistently reshaped the business, and what may be on the horizon. Drawing on historical parallels, Cohen examines how each decadeâs ânewâ disruptive formatâfrom FM radio to MP3âprovoked significant resistance within the industry until widespread consumer adoption necessitated transformation. By analysing current developments in AI, generative music, and large-scale data analytics through this perspective, Cohen emphasises that the music industryâs resilience has often stemmed from a willingness to embrace innovation rather than resist it. He highlights important misconceptions surrounding streaming services and emphasises musicâs broader social and economic advantages, referencing research by Shain Shapiro of Sound Diplomacy on how music contributes to urban development, employment, and cultural identity beyond its direct revenue. This relates to non-fungible tokens, blockchain, and emerging DAO (decentralised autonomous organisation) models. According to Cohen, these technologies can significantly enhance how creators license their work, track royalties in real-time, and transition from centralised gatekeepers to more collaborative, transparent relationships. In closing, Cohen reaffirms that significant labels will continue to evolve and maintain strong positions but must adopt a longer-term, adaptive mindset. The music industry, he argues, has shown time and again that while short-term protective strategies are common, lasting success stems from embracing new toolsâbe they streaming services, generative AI, or DAO-based platformsâand recalibrating them to uphold both cultural and economic value for all stakeholders.
Drone delivery services are encountering issues related to transparency, authenticity, and safeguarding privacy, highlighting the urgent need for an innovative approach that incorporates blockchain technology. This innovation aims to solidify the permanence of records, enable instantaneous verification, and streamline data handling in these intricate, self-operating transactions. In this paper, we use of blockchain for creating Non-Fungible Tokens (NFTs), which act as unalterable logs of purchase within the realm of delivery logistics. Our method adopts a distinctive two-fold strategy that places equal emphasis on both tangible goods and information. When integrating our solution with the Polygon network, we have achieved a substantial reduction in the costs associated with transactions while simultaneously enhancing the speed at which these transactions are processed. Our work not only addresses the existing challenges faced by unmanned aerial vehicle (UAV) communication systems but also sets a new standard for efficiency and security in the delivery logistics sector, paving the way for more reliable and transparent UAV-based delivery services.
Vivi Andersson, Sofia Bobadilla, Harald Hobbelhagen, Martin Monperrus
Smart contracts operate in a highly adversarial environment, where vulnerabilities can lead to substantial financial losses. Thus, smart contracts are subject to security audits. In auditing, proof-of-concept (PoC) exploits play a critical role by demonstrating to the stakeholders that the reported vulnerabilities are genuine, reproducible, and actionable. However, manually creating PoCs is time-consuming, error-prone, and often constrained by tight audit schedules. We introduce PoCo, an agentic framework that automatically generates executable PoC exploits from natural-language vulnerability descriptions written by auditors. PoCo autonomously generates PoC exploits in an agentic manner by interacting with a set of code-execution tools in a ReasonâActâObserve loop. It produces fully executable exploits compatible with the Foundry testing framework, ready for integration into audit reports and other security tools. We evaluate PoCo on a dataset of 23 real-world vulnerability reports. PoCo consistently outperforms the Zero-shot and Workflow baselines, generating well-formed and logically correct PoCs. Our results demonstrate that agentic frameworks can significantly reduce the effort required for high-quality PoCs in smart contract audits. Our contribution provides actionable knowledge for the smart contract security community.
With the introduction of blockchain technology and the emergence of non-fungible tokens (NFTs), users can prove ownership of digital content by cryptographically tokenizing the content they create, and it becomes possible to trade digital content. As user-generated digital content is frequently traded online, many scholars have analyzed the factors of user transactions, but there is a limitation that they have not been able to analyze the direct relationship between the sentiments of users and price. Therefore, this study uses multi-layer perceptron so as to analyze the factors that affect the price of profile picture (PFP) NFTs by using not only collectable market indicators and technical indicators but also sentiment indicators. As a result, it was found that PFP NFTs are closely correlated with various indicators, and a model was developed to accurately predict the price fluctuations of PFP NFTs using these indicators. The empirical results demonstrate that the proposed MLP model achieved prediction accuracies of 81.49% for BAYC and 93.39% for Cryptopunks. Furthermore, stock indices were found to exert a positive influence on NFT prices, whereas increases in cryptocurrency values, interest rates, and discussion volume acted as negative determinants. By contrast, the interaction of positive and objective sentiment contributed positively to price formation.
The integration of Uncrewed Aerial Vehicles (UAVs) into low-altitude airspace has led authorities to adopt distributed Uncrewed Traffic Management (UTM) architectures that ensure interoperability and safety. Blockchain has been proposed as an enabler for trustworthy coordination among UTM stakeholders. Yet, its real-time performance under aeronautical constraints remains insufficiently characterized. This paper presentes a quantitative benchmark comparing two regulation compliant distributed architectures: the federated InterUSS platform maintained by the Linux Foundation and a permissioned blockchain based on Hyperledger Fabric. Both systems were evaluated through Operational Intent Reference (OIR) registration work loads generated via Hyperledger Caliper, measuring throughput, latency, and transaction loss under loads up to 50 transactions per second. Results show that InterUSS sustained sub-second latency and stable performance up to 30 TPS. At the same time, Fabric exhibited exponential degradation with median latency exceeding 3 s and tail latencies above 15 s beyond that point. These findings demonstrate that blockchain-based architectures must be redesigned to meet aeronautical timing and scalability requirements, suggesting that hybrid models combining distributed ledgers for auditability with federated frameworks for real-time coordination are more suitable for future UTM deployments.
Metaverses have been hailed as the next arena for a wide spectrum of technovation and business opportunities. This research (â N = 714) focuses on the three underexplored areas of virtual commerce in AI-enabled metaverses: blockchain-powered cryptocurrencies, non-fungible tokens (NFTs), and AI-powered virtual influencers. Study 1 reports the mediating effects of (dis)trust in AI-enabled blockchain technologies and the moderating effects of consumersâ technopian perspectives in explaining the relationship between blockchain transparency perception and intention to use cryptocurrencies in AI-powered metaverses. Study 1 also reports the mediating effects of Neo-Luddism perspectives regarding metaverses and the moderating effects of consumersâ social phobia in explaining the relationship between AI-algorithm awareness and behavioral intention to engage with AI-powered virtual influencers in metaverses. Study 2 reports the serial mediating effects of general perception of NFT ownership and psychological ownership of NFTs as well as the moderating effects of the investment value of NFTs in explaining the relationship between acknowledgment of the nature of NFTs and intention to use NFTs in AI-enabled metaverses. Theoretical contributions to the literature on digital materiality and psychological ownership of blockchain/cryptocurrency-powered NFTs as emerging forms of digital consumption objects are discussed. Practical implications for NFT-based branding/entrepreneurship and creative industries in blockchain-enabled metaverses are provided.