Ambi Rachel Alex, Syed Hassan Imam Gardezi, P S Krishnendu, P. Aruna · 5 authors
The rapid expansion of the Internet of Things (IoT) has led to an unprecedented rise in interconnected devices, generating vast volumes of sensitive data that demand robust security and trust mechanisms. Traditional centralized architectures often struggle to ensure integrity, privacy, and resilience against single points of failure, making them unsuitable for next-generation IoT ecosystems. This paper proposes a blockchain-enabled decentralized trust framework to strengthen the security, transparency, and reliability of IoT networks. By integrating distributed ledger technology with lightweight consensus protocols, the framework establishes immutable device identities, secure data exchange, and automated access control without dependence on centralized authorities. The proposed approach enhances interoperability among heterogeneous IoT devices while minimizing latency and computational overhead. Experimental evaluation and comparative analysis demonstrate that the blockchain-based trust model effectively mitigates common threats such as data tampering, spoofing, and unauthorized access, paving the way for a scalable and trustworthy foundation for future IoT applications.
Chapter 5 synthesizes practical strategies, ethical frameworks, and policy recommendations for integrating Metaverse technologies into career development, building on Super&s;s ( 1980 ) career stages. It demonstrates how immersive environments, AI-driven mentorship, and blockchain-secured credentials enhance career exploration, skill acquisition, and lifelong learning while outlining best practices for implementation. Case studies illustrate virtual internships, AR/XR simulations for high-risk professions, and IoT-enabled haptic feedback devices that improve accessibility for individuals with disabilities, ensuring equitable access to Metaverse resources. Ethical considerations address data privacy, algorithmic bias, and the psychological impacts of prolonged virtual immersion. The discussion advocates for transparent AI systems audited for fairness in career recommendations, zero-knowledge proofs for privacy-preserving credential verification, and robust cybersecurity protocols to protect user data. Policy implications highlight updated regulatory frameworks for digital credentialing, intellectual property in virtual spaces, and cross-border recognition of Metaverse-acquired skills. The chapter calls for international collaboration to standardize ethical guidelines, mitigate the digital divide, and ensure marginalized populations benefit from Metaverse advancements. It provides educators, policymakers, and organizations with an actionable roadmap to balance innovation with critical analysis and foster equitable, sustainable career development in the digital age.
The industrial internet of things (IIoT) expanded fast as physical devices and systems were connected to the internet. However, this interconnectedness made IIoT systems vulnerable to hackers. Intrusion detection systems (IDSs) were put in place to detect and prevent such assaults. Nonetheless, attackers might circumvent IDSs by forging identities or interfering with recorded data. The article intended to improve IIoT security by achieving system confidentiality, integrity, availability, scalability, performance, and security. For IIoT security, the article developed a secure federated learning access control framework (SecureFLACF) linked with a blockchain-based IDS. SecureFLACF used blockchain to secure data collected by IDS, AES-256 encryption to secure stored data, zero-knowledge proof (ZKP) to validate user identities and manage data access, and a federated learning access control framework (FLACF) to train a machine learning model for intrusion detection. SecureFLACF developed as a viable solution for improving IIoT security, providing strong assurances for IDS data and access control using blockchain’s tamper-proof structure and AES-256 encryption. Furthermore, FLACF’s design allows private machine learning model training, ensuring data privacy as well as model fidelity. The framework’s usefulness was highlighted by its application in real-world circumstances, making it a cost-effective option for organisations of all sizes. This method not only strengthened IIoT systems against a wide range of cyber threats, but also stressed their dependability as a safeguard. SecureFLACF exhibited considerable promise for improving IIoT security across several dimensions by encapsulating practicability, cost-effectiveness, and dependability.
Purpose This synthesis paper consolidates expert analyses on the persistent challenges and emerging opportunities in disaster risk reduction (DRR) financing and governance, with a focus on Latin America and the Caribbean (LAC). It critiques current paradigms and proposes pathways to align DRR with sustainable development goals. Design/methodology/approach Drawing on contributions from nine DRR specialists, the study evaluates four thematic areas: (1) conceptual and governance barriers, (2) data gaps and analytical limitations, (3) financing mechanisms and (4) DRR-climate adaptation synergies. Findings Key challenges include sectoral silos that isolate DRR from development planning, perpetuating reactive over proactive risk management; data disparities, with hazard-focused metrics overshadowing vulnerability analysis and local-scale risk drivers; financing imbalances, where dedicated DRR funds and risk-transfer instruments (e.g. insurance) often neglect root-cause vulnerability reduction and missed synergies between DRR and climate adaptation, exacerbated by institutional fragmentation and “additionality” constraints in climate finance. Notable progress includes increased Ministry of Finance engagement and decentralized resilience models (e.g. social protection schemes). Originality/value This paper uniquely synthesizes multidisciplinary critiques to advocate for integrated governance that embeds DRR in sectoral development agendas; holistic financing combining corrective, prospective and compensatory measures and systemic risk analytics bridging climate adaptation and DRR.
Decentralization has emerged as a prominent strategy for health sector reform in low- and middle-income countries (LMICs), aiming to enhance service quality, efficiency, equity, and responsiveness. This study systematically reviews literature published between 2021 and 2025 to explore the role of decentralized health systems in shaping healthcare service quality across LMICs. Using PRISMA 2020 guidelines, 20 eligible studies were identified and analyzed from databases including PubMed, Scopus, Web of Science, and Google Scholar. Thematic synthesis of findings reveals mixed outcomes: while decentralization improves local responsiveness, enhances community engagement, and strengthens health system performance in some settings, it also exacerbates disparities in others due to uneven institutional capacity, limited fiscal resources, and fragmented coordination. Key performance areas identified include human resource deployment, financing, access to services, and equity in service delivery. The study emphasizes the significance of local capacity-building, efficient resource allocation, and integrated planning in attaining sustainable and equitable healthcare improvements within decentralized systems. This review provides practical insights for policymakers aiming to align decentralization strategies with health equity and service quality objectives.
Allan Lavell, Margaret Arnold, Stephen Bender, Charlotte Benson · 10 authors
Purpose This article aims to synthesize expert analyses on progress, challenges and innovations in disaster risk reduction (DRR) financing and investment since the Hyogo Framework (HF) (2005–2015). It highlights systemic barriers, emerging strategies and lessons for policymakers. Design/methodology/approach Contributions from nine DRR experts are analysed, focusing on historical trends, case studies (e.g. Kenya’s FLLoCA Program) and empirical data from regional initiatives like the InterAmerican Development Bank- IDB- Disaster Risk Management Index. Findings Key issues include persistent underfunding of corrective DRR, over-reliance on risk transfer mechanisms and siloed governance. Successful examples include decentralized climate finance models and parametric insurance innovations. The study underscores the need for intersectoral collaboration and political commitment to equity. Originality/value This work provides a multidisciplinary critique of DRR financing, integrating perspectives from economics, governance and climate adaptation. It offers actionable recommendations to align DRR with sustainable development agendas in Latin America and the Caribbean- LAC.
Binh Thanh Nguyen, Thanh Tuan Chu, Son Ha, Anh Tuan Nguyen
Purpose Our research augments the expanding body of literature concerning the capability of prevalent Large Language Models (LLM) tools in supporting financial professionals. We introduce a framework to leverage ChatGPT to assess market sentiment through the analysis of social media data. Design/methodology/approach We use the LLM models to construct market sentiment indicators based on Twitter tweets and use those indicators to explain Bitcoin return. Findings Our analysis uncovers that sentiment indicators crafted with ChatGPT4o/ChatGPT3.5 significantly affect Bitcoin returns, even when accounting for a broad array of control variables and other pre-established sentiment indicators. Originality/value These insights imply that ChatGPT4o/ChatGPT3.5 could empower financial professionals to discover sentiment information from Twitter tweets that were overlooked by previously introduced sentiment indicators concerning Bitcoin.
Khaleel Radhi Hasan Alzlzly, Basim Abdullah Kadhim, Rahim Raad Hameed, Hussein Basim Furaij
"The objective of this study is to analyze the impact of real-time public procurement disclosure through distributed ledger technology (DLT) on reducing the cost of bank financing for public projects in Iraq The importance of this research stems from the growing need to increase financial transparency and reduce information asymmetry between government entities and the banking sector, thereby reducing credit risk and funding a descriptive research." methodology such as An applied field design combining quantitative and qualitative approaches is supported. Data were collected through a structured questionnaire from a sample of 165 senior and middle managers from three major Iraqi banks (Al-Rafidin, Al-Rashid and Trade Bank of Iraq) that finance public projects. Used multiple linear regression and F/T tests to validate the study hypotheses. Had gone The findings show that real-time disclosure via DLT significantly reduces funding costs (α ≤ 0.05) by improving transparency and shortening contract verification cycles. Furthermore the availability of immutable, time-stamped purchasing data increased banks' trust in public agencies The study recommends that Iraq's Ministry of Finance and public procurement authorities improve the security of digital data and government and adopts a pilot DLT-based tender and contract management system with a legal framework to integrate banking platforms
An estimated 1.3 billion people worldwide (roughly 16% of the global population) are affected by various forms of disability. As highlighted by the World Health Organization, many face mobility-related challenges that significantly restrict their ability to participate fully in social and communal life. These restrictions hinder communication and reduce opportunities for linguistic and social enrichment. This study addresses these challenges by proposing Fairverse, an accessible metaverse designed to enhance socialization and inclusivity for people with physical disabilities. Using virtual reality (VR), blockchain and game technologies, Fairverse initially operates as a VR environment but also supports web-based access to ensure broader usability without specialized hardware. As a proof of concept, a customizable virtual room was developed that integrates Ready Player Me avatars and barrier-free avatars that can be controlled by voice commands. To ensure sustainable governance, a Decentralized Autonomous Organization (DAO) is proposed underpinned by a token economy, facilitating sponsorships and donations to incentivize content creators and virtual-world developers. By fostering an inclusive digital ecosystem, Fairverse aims to remove accessibility barriers in the virtual world, empowering users with disabilities to participate fully in the metaverse.
Andrés Fernández‐Miguel, Susana Ortíz-Marcos, Mariano Jiménez, Alfonso Pedro Fernández del Hoyo · 6 authors
This study advances toward establishing the theoretical foundations of Industry 6.0 by developing a comprehensive framework that integrates artificial intelligence (AI), decentralized control systems, and cyber–physical production environments for intelligent, sustainable, and adaptive manufacturing. The research employs a tri-modal methodology (deductive, inductive, and abductive reasoning) to construct a theoretical architecture grounded in five interdependent constructs: advanced technology integration, decentralized organizational structures, mass customization and sustainability strategies, cultural transformation, and innovation enhancement. Unlike prior conceptualizations of Industry 6.0, the proposed framework explicitly emphasizes the cyclical feedback between innovation and organizational design, as well as the role of cultural transformation as a binding element across technological, organizational, and strategic domains. The resulting framework demonstrates that AI-driven decentralized control systems constitute the cornerstone of Industry 6.0, enabling autonomous real-time decision-making, predictive zero-defect manufacturing, and strategic organizational agility through distributed intelligent control architectures. This work contributes foundational theory and actionable guidance for transitioning from centralized control paradigms to AI-driven distributed intelligent manufacturing control systems, establishing a conceptual foundation for the emerging Industry 6.0 paradigm.
Wencheng Chen, Jun Wang, Jeng‐Shyang Pan, R. Simon Sherratt · 5 authors
The explosive growth of Internet of Things (IoT) data demands secure and reliable storage, where traditional centralized solutions often fall short. Blockchain offers decentralization and tamper-resistance, making it a promising foundation for IoT. However, IoT blockchain systems based on Delegated Proof-of-Stake (DPoS) face challenges such as weak node incentives, unfair reward distribution, and low consensus efficiency. This paper proposes a fairness-aware incentive mechanism that accounts for both node capability and effort under information asymmetry. By incorporating fairness preferences into the contract design, the mechanism improves participation and motivates sustained effort. Theoretical analysis and simulation results show that our approach enhances throughput by about 15%, while achieving revenue fairness, incentive compatibility, and stronger consensus performance. The mechanism’s adaptability makes it suitable for diverse IoT application scenarios.
Kypros Iacovou, Georgia M. Kapitsaki, Evangelia Vanezi
Open Source Software (OSS) is widely used and carries licenses that indicate the terms under which the software is provided for use, also specifying modification and distribution rules. Ensuring that users are respecting OSS license terms when creating derivative works is a complex process. Compliance issues arising from incompatibilities among licenses may lead to legal disputes. At the same time, the blockchain technology with immutable entries offers a mechanism to provide transparency when it comes to licensing and ensure software changes are recorded. In this work, we are introducing an integration of blockchain and license management when creating derivative works, in order to tackle the issue of OSS license compatibility. We have designed, implemented and performed a preliminary evaluation of FOSS-chain, a web platform that uses blockchain and automates the license compliance process, covering 14 OSS licenses. We have evaluated the initial prototype version of the FOSS-chain platform via a small scale user study. Our preliminary results are promising, demonstrating the potential of the platform for adaptation on realistic software systems.
This research focuses on the design and development of a blockchain-based plastic waste tracking system aimed at enhancing transparency, efficiency, and accountability in plastic waste management. The system utilizes Hyperledger Fabric as a permissioned blockchain platform and integrates smart contracts to manage transactions between organizations, including waste generators, collectors, sorting warehouses, and final processing warehouses. This system records each stage of the plastic waste journey, from creation to final processing, in a permanent, transparent, and immutable manner. The testing results demonstrate that the system can accurately record the status and history of waste, manage transfers between organizations, and process plastic waste into recycled products. Moreover, the system shows a significant potential for carbon emission reduction, with an estimated reduction of up to 50% compared to traditional plastic waste management methods, such as incineration or landfilling. The study also explores how the implementation of blockchain can support global efforts in mitigating the environmental impacts of plastic waste. The blockchain-based system also provides real-time monitoring, ensuring that each transaction is verified and recorded immediately, contributing to more effective management. The implementation of smart contracts further guarantees that waste-related activities are executed automatically when predefined conditions are met, reducing administrative overhead. The study also explores how the implementation of blockchain can support global efforts in mitigating the environmental impacts of plastic waste. Ultimately, this system presents a scalable solution that could be adopted in various regions to improve global waste management strategies.
La tesi indaga come le primitive crittografiche sostengano sicurezza e integrità di Bitcoin, coniugando teoria e pratica. Si parte dai fondamenti (riservatezza, integrità, autenticazione, non ripudio) e dalle basi di complessità computazionale che giustificano la “one-wayness” degli algoritmi moderni. Vengono presentate cifratura simmetrica e asimmetrica, funzioni hash e l’algoritmo SHA-256 (double hashing), con cenni alla minaccia quantistica e agli standard post-quantum in via di adozione. Sul piano applicativo si descrive l’architettura: blockchain come registro append-only, Merkle tree e Merkle root per verifiche efficienti, gestione di chiavi e indirizzi; firme digitali ECDSA e l’evoluzione SegWit/Taproot con Schnorr e MAST, che riducono malleabilità e ingombro on-chain migliorando privacy ed efficienza. La sezione operativa tratta HD wallet (seed phrase, derivation paths) e schemi avanzati di firma a soglia, evidenziandone impatti su usabilità e rischio. La sicurezza di rete è analizzata attraverso i principali vettori d’attacco (double spending, 51%, address poisoning), il ruolo degli incentivi economici del mining e il retarget della difficoltà che stabilizza il tempo di blocco. Per la privacy si distinguono pseudonimia e anonimato e si valutano tecniche on/off-chain: CoinJoin/PayJoin, Stonewall(x2), Dandelion++ e Lightning Network; si discutono anche Zero-Knowledge Proofs e Self-Sovereign Identity con DIDs/VCs e cornice eIDAS. Infine si affronta la scalabilità: trilemma sicurezza-decentralizzazione-throughput, ottimizzazioni on-chain (SegWit) e soluzioni Layer-2 (Lightning, sidechain), insieme alla governance degli aggiornamenti tramite soft e hard fork. Conclusione: un modello modulare in cui il Layer 1 resta strato di regolamento sicuro, mentre Layer-2 e nuove primitive crittografiche abilitano efficienza, privacy e resilienza nel lungo periodo.
A. G. Ramakrishnan, Shubham Agarwal, Sharmila Kumari Selvanayagam, Kunwar P. Singh
As image generation models grow increasingly powerful and accessible, concerns around authenticity, ownership, and misuse of synthetic media have become critical. The ability to generate lifelike images indistinguishable from real ones introduces risks such as misinformation, deepfakes, and intellectual property violations. Traditional watermarking methods either degrade image quality, are easily removed, or require access to confidential model internals – making them unsuitable for secure and scalable deployment. We are the first to introduce ZK-WAGON, a novel system for watermarking image generation models using the Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARKs). Our approach enables verifiable proof of origin without exposing model weights, generation prompts, or any sensitive internal information. We propose Selective Layer ZK-Circuit Creation (SL-ZKCC), a method to selectively convert key layers of an image generation model into a circuit, reducing proof generation time significantly. Generated ZK-SNARK proofs are imperceptibly embedded into a generated image via Least Significant Bit (LSB) steganography. We demonstrate this system on both GAN and Diffusion models, providing a secure, model-agnostic pipeline for trustworthy AI image generation.
Open access
2 source records
Physical Unclonable Functions (PUFs) and Hardware Security
Adversarial Robustness in Machine Learning
Generative Adversarial Networks and Image Synthesis
The article presents a comprehensive study of the phenomenon of digital identity in the context of contemporary challenges to the protection and safeguarding of human rights under conditions of global digital transformation and the rapid development of virtual environments. It is emphasized that the growing scale of the collection and processing of personal and confidential data, the increasing reliance on algorithmic decision-making systems, and the gradual displacement of direct human involvement in identification and control processes highlight the need to reconsider conceptual, legal, and ethical approaches to the regulation of digital identity. It is established that the right to identity still lacks unified recognition in international legal instruments, resulting in multiple doctrinal approaches—ranging from its understanding as an autonomous subjective right to its definition as a tool for accessing other rights or even as a potential threat to their realization. The evolution of digital identity is traced from basic authentication mechanisms to multi-layered structures integrating personal characteristics, behavioral patterns, biometric data, and users’ digital footprints. Key risks are identified, including discrimination, social exclusion of vulnerable groups, unjustified profiling, excessive surveillance, misuse of data, and the potential use of identification systems as tools of political or social pressure. The positions of international institutions on the conceptualization of digital identity and its relationship with human rights are analyzed. Promising technological solutions for balancing security and privacy are proposed, including decentralized blockchain-based identification with integrated smart contracts, zero-knowledge proof protocols, biometric verification, and verified account labeling. It is argued that the optimal model of digital identification in virtual environments should combine technological reliability, flexibility, ethical soundness, and compliance with international standards, ensuring a balance between the right to privacy, effective authentication, and the preservation of user trust in digital infrastructure.
Legal, Health, Environmental and COVID-19 Challenges
Alex Brockbank, Charlene M. Kalenkoski, Christopher R. Browning, Michael Guillemette
Do financial advisors recommend cryptocurrency investment within a household portfolio? Cryptocurrencies have emerged in popularity as households seek to maximize returns. Financial advisors are expected to provide beneficial advice for a household in managing financial decisions including investments. The existing literature has examined this relatively new form of investing and found some determinants for cryptocurrency investment but has not sufficiently explored the association between this investment option and the investor’s use of a financial advisor. With data from the 2018 wave of the National Financial Capabilities Study (NFCS), this paper examines the relationship between cryptocurrency investment and the use of a financial advisor for American investors. The results suggest that investors who use a financial advisor are more likely to be invested in cryptocurrencies. Additional determinants seen in previous works are also confirmed in the current study; showing that men, younger investors, married investors, and investors with a higher tolerance for risk are more likely to have cryptocurrency investments.
The article presents a comprehensive study of the phenomenon of digital identity in the context of contemporary challenges to the protection and safeguarding of human rights under conditions of global digital transformation and the rapid development of virtual environments. It is emphasized that the growing scale of the collection and processing of personal and confidential data, the increasing reliance on algorithmic decision-making systems, and the gradual displacement of direct human involvement in identification and control processes highlight the need to reconsider conceptual, legal, and ethical approaches to the regulation of digital identity. It is established that the right to identity still lacks unified recognition in international legal instruments, resulting in multiple doctrinal approaches—ranging from its understanding as an autonomous subjective right to its definition as a tool for accessing other rights or even as a potential threat to their realization. The evolution of digital identity is traced from basic authentication mechanisms to multi-layered structures integrating personal characteristics, behavioral patterns, biometric data, and users’ digital footprints. Key risks are identified, including discrimination, social exclusion of vulnerable groups, unjustified profiling, excessive surveillance, misuse of data, and the potential use of identification systems as tools of political or social pressure. The positions of international institutions on the conceptualization of digital identity and its relationship with human rights are analyzed. Promising technological solutions for balancing security and privacy are proposed, including decentralized blockchain-based identification with integrated smart contracts, zero-knowledge proof protocols, biometric verification, and verified account labeling. It is argued that the optimal model of digital identification in virtual environments should combine technological reliability, flexibility, ethical soundness, and compliance with international standards, ensuring a balance between the right to privacy, effective authentication, and the preservation of user trust in digital infrastructure.
Edgar Roberto Dulce Villarreal, Julio Ariel Hurtado Alegría, José García-Alonso
Interoperability between blockchain platforms remains a key challenge, particularly in sensitive domains such as healthcare, where the secure and consistent exchange of clinical information between institutions is essential. While technical interoperability solutions exist, semantic interoperability at the level of smart contracts continues to be a significant limitation. This paper presents MUISCA, a mechanism based on Model-Driven Engineering that enables the automatic generation of interoperable smart contracts across different blockchain platforms. By defining metamodels, abstract models, and transformation rules, MUISCA produces platform-specific code for technologies such as Ethereum and Hyperledger Fabric. The mechanism was validated through a healthcare case study focused on patient transfers between medical institutions, demonstrating its ability to support the secure exchange of clinical data. Additionally, its acceptance was evaluated through expert surveys assessing perceived usefulness and ease of use. Results show that MUISCA improves smart contract portability, reduces implementation errors, and enhances system security. The proposed solution contributes to advancing semantic interoperability in blockchain-based health information systems and provides a foundation for broader application in other critical domains that require high levels of integration and data protection.
Marta Spyra, Rafał Balina, Marta Idasz-Balina, Adam Zając · 5 authors
As the global economy undergoes rapid digital transformation, cryptocurrencies have emerged as a prominent alternative class of financial assets. Their decentralized nature, pseudonymity, and lack of centralized oversight have attracted considerable interest among investors while simultaneously raising significant concerns among regulators and compliance professionals. While cryptocurrencies offer benefits such as enhanced accessibility and transactional privacy, they also pose notable risks, particularly their potential misuse in financial crimes, including money laundering. This study explores the perceived risks associated with cryptocurrencies in the context of money laundering, drawing on insights from a survey conducted among 50 financial sector professionals. A quantitative research design was employed, using a structured online questionnaire to assess participants’ awareness, investment behavior, and perceptions of the role of cryptocurrencies in illicit finance and financial system security. The results reveal a complex perspective: while 70% of respondents acknowledged the potential for cryptocurrencies to facilitate money laundering, 60% expressed support for their wider adoption. Notably, statistically significant correlations emerged between active investment in cryptocurrencies and the belief that they could enhance financial market security and reduce laundering risks. However, self-reported knowledge levels and general awareness did not show a significant relationship with perceived risk. The findings underscore the importance of a balanced approach to regulation, one that fosters innovation while mitigating illicit finance risks. The study recommends increased investment in user education, the development of blockchain analytics, the adoption of global regulatory standards and enhanced international cooperation to ensure the responsible evolution of the cryptocurrency ecosystem.