Search Results (304)

The COVID-19 outbreak significantly impacted global health, resulting in widespread infections and fatalities. In response, the World Health Organization (WHO) launched the Preparedness and Resilience for Emerging Threats (PRET) program, focusing on respiratory pathogens, to prepare for future pandemics and achieve sustainable well-being around the world. Moreover, the WHO also encouraged countries to establish a National Action Plan for Health Security (NAPHS) to address various disasters and threats. Therefore, governments should develop the necessary systems aligned with NAPHS while maintaining compliance with PRET. Thus, to maintain global health and wellness, a platform for sharing medical data on highly contagious diseases worldwide, free from interference from individual countries, is critical for effective border control. In this paper, we introduce an efficient approach, i.e., a two-layer decentralized blockchain architecture. Our mechanism streamlines integration between national sovereignty and the WHO, enabling the secure and supervised exchange of pandemic data via a single global blockchain and multiple local blockchains. This blockchain framework has strong potential to enhance nations’ ability to prepare for and respond to future pandemics, ensuring the safety and health of their citizens. The bottom-layer local chains facilitate the collection of pandemic immunity data within their own countries, and the upper-layer global chain, with the assistance of the WHO, facilitates the worldwide exchange of these data if needed. Given the characteristics of decentralization and transparency in blockchain technology, and the WHO’s oversight, no government should worry that sensitive medical data will be manipulated or abused by superpowers on the global blockchain. It also highlights the importance of global collaboration in preventing and controlling contagious diseases. Furthermore, the performance of this system is assessed based on several sets of real-world data and requirements. We demonstrate that this global information-sharing mechanism can improve international health safety, provided it is supported by feasible and reasonable resources to handle transactional demands around the world. Full article

Unmanned Aerial Vehicles (UAVs) are increasingly integrated into Internet of Things (IoT) ecosystems for applications such as surveillance, disaster response, environmental monitoring, and logistics. These missions demand reliable and secure communication between UAVs and cloud platforms for command, control, and data storage. However, UAV communication channels are highly vulnerable to eavesdropping, spoofing, and man-in-the-middle attacks due to their wireless and often long-range nature. Traditional cryptographic schemes either impose excessive computational overhead on resource-constrained UAVs or lack sufficient robustness for cloud-level security. To address this challenge, we propose a dual-layer encryption architecture that balances lightweight efficiency with strong cryptographic guarantees. Unlike prior dual-layer approaches, the proposed framework introduces a context-aware adaptive lightweight layer for UAV-to-gateway communication and a hybrid post-quantum layer for gateway-to-cloud security, enabling dynamic cipher selection, energy-aware key scheduling, and quantum-resilient key establishment. In the first layer, UAV-to-gateway communication employs a lightweight symmetric encryption scheme optimized for low latency and minimal energy consumption. In the second layer, gateway-to-cloud communication uses post-quantum asymmetric encryption to ensure resilience against emerging quantum threats. The architecture is further reinforced with optional multi-path hardening and blockchain-assisted key lifecycle management to enhance scalability and tamper-proof auditability. Experimental evaluation using a UAV testbed and cloud integration shows that the proposed framework achieves 99.85% confidentiality preservation, reduces computational overhead on UAVs by 42%, and improves end-to-end latency by 35% compared to conventional single-layer encryption schemes. These results confirm that the proposed adaptive and hybridized dual-layer design provides a scalable, secure, and resource-aware solution for UAV-to-cloud communication, offering both present-day practicality and future-proof cryptographic resilience. Full article

Blockchain is increasingly applied in the agri-food sector to enhance traceability, data integrity, and accountability. However, its broader role in food system sustainability remains insufficiently characterized, particularly when examined against global megatrends shaping future agri-food transitions. This paper investigates how blockchain technology can reinforce sustainable, inclusive, and resilient food systems under the effect of major global megatrends. A structured literature review of peer-reviewed and industry sources was conducted to identify evidence on blockchain-enabled improvements in transparency, certification, and supply chain coordination. Complementary analysis of a curated dataset of European and international pilot implementations evaluated technological architectures, governance models, and demonstrated performance outcomes. Additionally, stakeholder-based foresight activities and scenarios representing alternative blockchain adoption pathways, developed within the TRUSTyFOOD project (GA: 101060534), were used to examine the interconnection between blockchain adoption and megatrends. Evidence from the literature and pilot cases indicates that blockchain can strengthen product-level traceability and improve verification of sustainability and safety claims. Cross-case analysis also reveals persistent constraints, including heterogeneous technical standards, limited interoperability, high deployment costs for smallholders, and governance risks arising from consortium-led platforms. Blockchain can function as an enabling digital layer for sustainable and resilient food systems and should be embedded in wider, participatory strategies that align digital innovation with long-term sustainability and equity goals in the agri-food sector. Full article

The integration of Software-Defined Networking (SDN), blockchain (BC), and machine learning (ML) has emerged as a promising approach to securing Internet of Things (IoT) and Industrial IoT (IIoT) networks. This paper conducted a comprehensive review of recent studies focusing on multi-layered security across device, control, network, and application layers. The analysis reveals that BC technology ensures decentralised trust, immutability, and secure access validation, while SDN enables programmability, load balancing, and real-time monitoring. In addition, ML/deep learning (DL) techniques, including federated and hybrid learning, strengthen anomaly detection, predictive security, and adaptive mitigation. Reported evaluations show similar gains in detection accuracy, latency, throughput, and energy efficiency, with effective defence against threats, though differing experimental contexts limit direct comparison. It also shows that the solutions’ effectiveness depends on ecosystem factors such as SDN controllers, BC platforms, cryptographic protocols, and ML frameworks. However, most studies rely on simulations or small-scale testbeds, leaving large-scale and heterogeneous deployments unverified. Significant challenges include scalability, computational and energy overhead, dataset dependency, limited adversarial resilience, and the explainability of ML-driven decisions. Based on the findings, future research should focus on lightweight consensus mechanisms for constrained devices, privacy-preserving ML/DL, and cross-layer adversarial-resilient frameworks. Advancing these directions will be important in achieving scalable, interoperable, and trustworthy SDN-IoT/IIoT security solutions. Full article

Digital transformation in port logistics represents a profound and systemic shift in the way maritime trade and supply chain operations are designed, coordinated, and governed through the pervasive integration of advanced digital technologies and data-driven management practices. It extends beyond the mere digitization of paper-based documents into electronic formats and beyond the digitalization of isolated processes with IT tools. Transformation involves reconfiguring organizational structures, decision-making logics, and value creation models around connectivity, automation, and predictive intelligence. In practice, it includes the adoption of smart port technologies such as the Internet of Things, 5G communication networks, digital twins, blockchain-based trade documentation, and artificial intelligence applied to vessel scheduling and cargo planning. It also encompasses collaborative platforms like port community systems that link shipping companies, terminal operators, freight forwarders, customs, and hinterland transport providers into data-driven ecosystems. The purpose of digital transformation is not only to improve efficiency and reduce operational bottlenecks, but also to enhance resilience against disruptions, ensure sustainability in line with decarbonization goals, and reposition ports as orchestrators of trade networks rather than passive providers of physical infrastructure. Full article

The temperate Himalayan states of Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Ladakh, Sikkim, and Arunachal Pradesh in India face unique agro-ecological challenges across agriculture and allied sectors, including pest and disease pressures, inefficient resource use, post-harvest losses, and fragmented supply chains. This review systematically examines 21 critical problem areas, with three key challenges identified per sector across agriculture, agricultural engineering, fisheries, forestry, horticulture, sericulture, and animal husbandry. Artificial Intelligence (AI) and Machine Learning (ML) interventions, including computer vision, predictive modeling, Internet of Things (IoT)-based monitoring, robotics, and blockchain-enabled traceability, are evaluated for their regional applicability, pilot-level outcomes, and operational limitations under temperate Himalayan conditions. The analysis highlights that AI-enabled solutions demonstrate strong potential for early pest and disease detection, improved resource-use efficiency, ecosystem monitoring, and market integration. However, large-scale adoption remains constrained by limited digital infrastructure, data scarcity, high capital costs, low digital literacy, and fragmented institutional frameworks. The novelty of this review lies in its cross-sectoral synthesis of AI/ML applications tailored to the Himalayan context, combined with a sector-wise revenue-loss assessment to quantify economic impacts and guide prioritization. Based on the identified gaps, the review proposes feasible, context-aware strategies, including lightweight edge-AI models, localized data platforms, capacity-building initiatives, and policy-aligned implementation pathways. Collectively, these recommendations aim to enhance sustainability, resilience, and livelihood security across agriculture and allied sectors in the temperate Himalayan region. Full article

As global supply chains face increasing pressure to reconcile economic efficiency, environmental responsibility, and ethical transparency, emerging digital technologies offer unprecedented opportunities for sustainable transformation. This article examines this dynamic in the context of the Moroccan industrial sector, with particular reference to blockchain and digital twin technologies. The study employs a rigorous mixed-methods design, combining an in-depth qualitative exploration with 30 industry professionals and a Partial Least Squares Structural Equation Modeling (PLS-SEM) model based on survey data from 125 Moroccan manufacturing firms. The findings highlight the synergistic contribution of blockchain and digital twins in enabling circular, low-carbon, and resilient supply chains. Blockchain adoption strengthens environmental impact traceability, data reliability, and responsible governance, while digital twin systems enhance eco-efficiency through real-time modeling and predictive flow simulation. Circular integration emerges as a critical enabler, significantly amplifying the positive effects of both technologies by aligning physical and informational flows within closed-loop processes. With its strong empirical grounding and contextual relevance to an emerging economy, this research provides actionable insights for policymakers, industrial managers, and supply chain practitioners committed to accelerating the sustainable transformation of production systems. It also offers a renewed understanding of how digitalization and circularity jointly support environmental performance within industrial ecosystems. Full article

The increasing deployment of interconnected devices in Smart Cities and Industrial Internet of Things (IIoT) environments has significantly enhanced operational efficiency, automation, and real-time data analytics. However, this rapid digitization also introduces complex security and privacy challenges, particularly in the handling of sensitive data across heterogeneous and resource-constrained networks. This review explores the current landscape of privacy-preserving protocols designed for Smart City and IIoT infrastructures. We examine state-of-the-art approaches including lightweight cryptographic schemes, secure data aggregation, anonymous communication protocols, and blockchain-based frameworks. The paper also analyzes practical trade-offs between security, latency, and computational overhead in real-world deployments. Open research challenges such as secure interoperability, privacy in federated learning, and resilience against AI-driven cyberattacks are discussed. Finally, the paper outlines promising research directions and technologies that can enable scalable, secure, and privacy-aware network infrastructures for future urban and industrial ecosystems. Full article

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT), known as Artificial Intelligence of Things (AIoT), has emerged as a transformative paradigm for enabling intelligent, data-driven, and context-aware decision-making in urban environments to reduce the carbon footprint of mobility and industry. This review examines the conceptual foundations, and state-of-the-art developments of AIoT, with a particular emphasis on its applications in smart cities and its relevance to climate change management. AIoT integrates sensing, connectivity, and intelligent analytics to provide optimized solutions in transportation systems, energy management, waste collection, and environmental monitoring, directly influencing urban sustainability. Beyond urban efficiency, AIoT can play a critical role in addressing the global challenges and management of climate change by (a) precise measurements and autonomously remote monitoring; (b) real-time optimization in renewable energy distribution; and (c) developing prediction models for early warning of climate disasters. This paper performs a literature review and bibliometric analysis to identify the current landscape of AIoT research in smart city contexts. Over 1885 articles from Web of Sciences and over 1854 from Scopus databases, published between 1993 and January 2026, were analyzed. The results reveal a strong and accelerating growth in research activity, with publication output doubling in the most recent two years compared to 2023. Waste management and air quality monitoring have emerged as leading application domains, where AIoT-based optimization and predictive models demonstrate measurable improvements in operational efficiency and environmental impact. Altogether, these support faster and more effective decisions for reducing greenhouse gas emissions and ensuring the sustainable use of resources. The reviewed studies reveal rapid advancements in edge intelligence, federated learning, and secure data sharing through the integration of AIoT with blockchain technologies. However, significant challenges remain regarding scalability, interoperability, privacy, ethical governance, and the effective translation of research outcomes into policy and citizen-oriented tools such as climate applications, insurance models, and disaster alert systems. By synthesizing current research trends, this article highlights the potential of AIoT to support sustainable, resilient, and citizen-centric smart city ecosystems while identifying both critical gaps and promising directions for future investigations. Full article

Secure and auditable data sharing in large-scale Internet of Things (IoT) environments remains a significant challenge due to weak trust coordination, limited scalability, and susceptibility to emerging quantum attacks. This study introduces a hybrid blockchain-based framework that integrates post-quantum cryptography with intelligent anomaly detection to ensure end-to-end data integrity and resilience. The proposed system utilizes Hyperledger Fabric for permissioned device lifecycle management and Ethereum for public auditability of encrypted telemetry, thereby providing both private control and transparent verification. Device identities are established using quantum-entropy-seeded credentials and safeguarded with lattice-based encryption to withstand quantum adversaries. A convolutional long short-term memory (CNN–LSTM) model continuously monitors device behavior, facilitating real-time trust scoring and autonomous revocation via smart contract triggers. Experimental results demonstrate 97.4% anomaly detection accuracy and a 0.968 F1-score, supporting up to 1000 transactions per second with cross-chain latency below 6 s. These findings indicate that the proposed architecture delivers scalable, quantum-resilient, and computationally efficient data sharing suitable for mission-critical IoT deployments. Full article

Rapid decarbonization and decentralization of power systems are driving the integration of renewable generation, energy storage and digital technologies into unified energy ecosystems. In this context, photovoltaic (PV) systems combined with battery and hydrogen storage and blockchain-based platforms represent a promising pathway toward sustainable and transparent energy management. This study evaluates the techno-economic performance and operational feasibility of integrated PV systems combining battery and hydrogen storage with a blockchain-based peer-to-peer (P2P) energy trading platform. A simulation framework was developed for two representative consumer profiles: a scientific–educational institution and a residential household. Technical, economic and environmental indicators were assessed for PV systems integrated with battery and hydrogen storage. The results indicate substantial reductions in grid electricity demand and CO₂ emissions for both profiles, with hydrogen integration providing additional peak-load stabilization under current cost constraints. Blockchain functionality was validated through smart contracts and a decentralized application, confirming the feasibility of P2P energy exchange without central intermediaries. Grid electricity consumption is reduced by up to approximately 45–50% for residential users and 35–40% for institutional buildings, accompanied by CO₂ emission reductions of up to 70% and 38%, respectively, while hydrogen integration enables significant peak-load reduction. Overall, the results demonstrate the synergistic potential of integrating PV generation, battery and hydrogen storage and blockchain-based trading to enhance energy independence, reduce emissions and improve system resilience, providing a comprehensive basis for future pilot implementations and market optimization strategies. Full article

Reliable data availability and transparent governance are fundamental requirements for distributed edge-to-cloud systems that must operate across multiple administrative domains. Conventional cloud-centric architectures centralize control and storage, creating bottlenecks and limiting autonomous collaboration at the network edge. This paper introduces a decentralized governance and service-management framework that leverages Decentralized Autonomous Organizations (DAOs) and Decentralized Applications (DApps) to to govern and orchestrate verifiable, tamper-resistant, and continuously accessible data exchange between heterogeneous edge and cloud components. By embedding blockchain-based smart contracts within swarm-enabled edge infrastructures, the approach enables automated decision-making, auditable coordination, and fault-tolerant data sharing without relying on trusted intermediaries. The proposed OASEES framework demonstrates how DAO-driven orchestration can enhance data availability and accountability in real-world scenarios, including energy grid balancing, structural safety monitoring, and predictive maintenance of wind turbines. Results highlight that decentralized governance mechanisms enhance transparency, resilience, and trust, offering a scalable foundation for next-generation edge-to-cloud data ecosystems. Full article

The convergence of artificial intelligence (AI), machine learning (ML), blockchain, and big data analytics is transforming the governance, sustainability, and resilience of modern banking ecosystems. This study provides a multivariate bibliometric analysis using Principal Component Analysis (PCA) of research indexed in Scopus and Web of Science to explore how decentralized digital infrastructures and AI-driven analytical capabilities contribute to sustainable financial development, transparent governance, and climate-resilient digital societies. Findings indicate a rapid increase in interdisciplinary work integrating Distributed Ledger Technology (DLT) with large-scale data processing, federated learning, privacy-preserving computation, and intelligent automation—tools that can enhance financial inclusion, regulatory integrity, and environmental risk management. Keyword network analyses reveal blockchain’s growing role in improving data provenance, security, and trust—key governance dimensions for sustainable and resilient financial systems—while AI/ML and big data analytics dominate research on predictive intelligence, ESG-related risk modeling, customer well-being analytics, and real-time decision support for sustainable finance. Comparative analyses show distinct emphases: Web of Science highlights decentralized architectures, consensus mechanisms, and smart contracts relevant to transparent financial governance, whereas Scopus emphasizes customer-centered analytics, natural language processing, and high-throughput data environments supporting inclusive and equitable financial services. Patterns of global collaboration demonstrate strong internationalization, with Europe, China, and the United States emerging as key hubs in shaping sustainable and digitally resilient banking infrastructures. By mapping intellectual, technological, and collaborative structures, this study clarifies how decentralized intelligence—enabled by the fusion of AI/ML, blockchain, and big data—supports secure, scalable, and sustainability-driven financial ecosystems. The results identify critical research pathways for strengthening financial governance, enhancing climate and social resilience, and advancing digital transformation, which contributes to more inclusive, equitable, and sustainable societies. Full article

A key component of creating robust and sustainable businesses is the digital transformation of business operations. This study examines the impact of distributed digital technology, namely cloud computing and blockchain technology, on an auditor’s behavior, an essential component of the framework for corporate responsibility. This study also highlights the impact of digital transformation on sustainable auditing, urging auditors to improve their technological skills to build trust in evolving entities. We used a unique dataset of Chinese A-share listed companies from 2013 to 2021 to show that this time period is important because it shows the beginning and growth of these technologies in the Chinese business world. This gives us a good starting point for looking at their early-stage audit effects. Our key findings are threefold. First, we found that firms using distributed digital technologies (cloud computing and blockchain) experienced (a) higher audit fees and (b) standard audit opinions, indicating the growing complexity and the requirement that auditors acquire specialized skills in order to evaluate cyber-resilience and technological structures. Second, firms facing substantial profit fluctuations (higher risk level) following digital engagement were subject to higher audit fees and a decreased probability of standard audit outcomes, emphasizing the nuanced risks of digital transformation. Third, the main results were more pronounced in (a) non-state-owned enterprises and (b) high-tech enterprises. Our study is robust to multiple sensitivity analyses, endogeneity tests, and propensity score matching (PSM). The results show that regulators need to create and support specialized auditing regulations regarding distributed technologies. These regulations would assist auditors in evaluating cloud and blockchain engagement and make it clear to businesses what is important to be compliant. Full article

Zero-Touch Network (ZTN) represents a cornerstone approach of Next Generation Networks (NGNs), enabling fully automated and AI-driven network and service management. However, their distributed and multi-domain nature introduces critical security challenges, particularly regarding service identity and data integrity. This paper proposes a novel blockchain-based framework to enhance the security of ZTN through two complementary mechanisms: decentralized digital identity management and oracle-assisted network monitoring. First, a Decentralized Identity Management framework aligned with Zero-Trust Architecture principles is introduced to ensure tamper-proof authentication and authorization in a trustless environment among network components. By leveraging decentralized identifiers, verifiable credentials, and zero-knowledge proofs, the proposed Decentralized Authentication and Authorization component eliminates reliance on centralized authorities, while preserving privacy and interoperability across domains. Second, the paper investigates blockchain oracle mechanisms as a means to extend data integrity guarantees beyond the blockchain, enabling secure monitoring of Network Services and validation of Service-Level Agreements. We propose a four-dimensional framework for oracle design, based on qualitative comparison of oracle types—decentralized, compute-enabled, and consensus-based—to identify their suitability for NGN scenarios. This work proposes an architectural and design framework for Zero-Touch Networks, focusing on system integration and security-aware orchestration rather than large-scale experimental evaluation. The outcome of our study highlights the potential of integrating blockchain-based identity and oracle solutions to achieve resilient, transparent, and self-managed network ecosystems. This research bridges the gap between theory and implementation by offering a holistic approach that unifies identity security and data integrity in ZTNs, paving the way towards trustworthy and autonomous 6G infrastructures. Full article