Search Results (14)

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

Secure authentication in vehicular ad hoc networks (VANETs) remains a fundamental challenge due to their dynamic topology, susceptibility to attacks, and scalability constraints in multi-hop communication. Existing approaches based on elliptic curve cryptography (ECC), blockchain, and fog computing have achieved partial success but suffer from latency, resource overhead, and limited adaptability, leaving a gap for lightweight and hardware-rooted trust models. To address this, we propose a multi-hop mutual authentication protocol leveraging Physical Unclonable Functions (PUFs), which provide tamper-evident, device-specific responses for cryptographic key generation. Our design introduces a structured sequence of phases, including pre-deployment, registration, login, authentication, key establishment, and session maintenance, with optional multi-hop extension through relay vehicles. Unlike prior schemes, our protocol integrates fuzzy extractors for error tolerance, employs both inductive and game-based proofs for security guarantees, and maps BAN-logic reasoning to specific attack resistances, ensuring robustness against replay, impersonation, and man-in-the-middle attacks. The protocol achieves mutual trust between vehicles and RSUs while preserving anonymity via temporary identifiers and achieving forward secrecy through non-reused CRPs. Conceptual comparison with state-of-the-art PUF-based and non-PUF schemes highlights the potential for reduced latency, lower communication overhead, and improved scalability via cloud-assisted CRP lifecycle management, while pointing to the need for future empirical validation through simulation and prototyping. This work not only provides a secure and efficient solution for VANET authentication but also advances the field by offering the first integrated taxonomy-driven evaluation of PUF-enabled V2X protocols in multi-hop Wi-Fi environments. Full article

As vital material carriers of human civilization, earthen sites are experiencing continuous surface deterioration under the combined effects of weathering and anthropogenic damage. Traditional surface conservation techniques, due to their poor compatibility and limited reversibility, struggle to address the compound challenges of micro-scale degradation and macro-scale deformation. With the deep integration of digital twin technology, spatial information technologies, intelligent systems, and sustainable concepts, earthen site surface conservation technologies are transitioning from single-point applications to multidimensional integration. However, challenges remain in terms of the insufficient systematization of technology integration and the absence of a comprehensive interdisciplinary theoretical framework. Based on the dual-core databases of Web of Science and Scopus, this study systematically reviews the technological evolution of surface conservation for earthen sites between 2000 and 2025. CiteSpace 6.2 R4 and VOSviewer 1.6 were used for bibliometric visualization analysis, which was innovatively combined with manual close reading of the key literature and GPT-assisted semantic mining (error rate < 5%) to efficiently identify core research themes and infer deeper trends. The results reveal the following: (1) technological evolution follows a three-stage trajectory—from early point-based monitoring technologies, such as remote sensing (RS) and the Global Positioning System (GPS), to spatial modeling technologies, such as light detection and ranging (LiDAR) and geographic information systems (GIS), and, finally, to today’s integrated intelligent monitoring systems based on multi-source fusion; (2) the key surface technology system comprises GIS-based spatial data management, high-precision modeling via LiDAR, 3D reconstruction using oblique photogrammetry, and building information modeling (BIM) for structural protection, while cutting-edge areas focus on digital twin (DT) and the Internet of Things (IoT) for intelligent monitoring, augmented reality (AR) for immersive visualization, and blockchain technologies for digital authentication; (3) future research is expected to integrate big data and cloud computing to enable multidimensional prediction of surface deterioration, while virtual reality (VR) will overcome spatial–temporal limitations and push conservation paradigms toward automation, intelligence, and sustainability. This study, grounded in the technological evolution of surface protection for earthen sites, constructs a triadic framework of “intelligent monitoring–technological integration–collaborative application,” revealing the integration needs between DT and VR for surface technologies. It provides methodological support for addressing current technical bottlenecks and lays the foundation for dynamic surface protection, solution optimization, and interdisciplinary collaboration. Full article

The Fourth Industrial Revolution and artificial intelligence (AI) technology are driving the transformation of the meat industry from mechanization and automation to intelligence and digitization. This paper provides a systematic review of key technological innovations in this field, including physical technologies (such as smart cutting precision improved to the millimeter level, pulse electric field sterilization efficiency exceeding 90%, ultrasonic-assisted marinating time reduced by 12 h, and ultra-high-pressure processing extending shelf life) and digital technologies (IoT real-time monitoring, blockchain-enhanced traceability transparency, and AI-optimized production decision-making). Additionally, it explores the potential of alternative meat production technologies (cell-cultured meat and 3D bioprinting) to disrupt traditional models. In application scenarios such as central kitchen efficiency improvements (e.g., food companies leveraging the “S2B2C” model to apply AI agents, supply chain management, and intelligent control systems, resulting in a 26.98% increase in overall profits), end-to-end temperature control in cold chain logistics (e.g., using multi-array sensors for real-time monitoring of meat spoilage), intelligent freshness recognition of products (based on deep learning or sensors), and personalized customization (e.g., 3D-printed customized nutritional meat products), these technologies have significantly improved production efficiency, product quality, and safety. However, large-scale application still faces key challenges, including high costs (such as the high investment in cell-cultured meat bioreactors), lack of standardization (such as the absence of unified standards for non-thermal technology parameters), and consumer acceptance (surveys indicate that approximately 41% of consumers are concerned about contracting illnesses from consuming cultured meat, and only 25% are willing to try it). These challenges constrain the economic viability and market promotion of the aforementioned technologies. Future efforts should focus on collaborative innovation to establish a truly intelligent and sustainable meat production system. Full article

Among searchable encryption techniques, multi-user dynamic searchable encryption (MUDSE) schemes are an important research direction. After the data owner transfers data to the cloud, it may be necessary to authorize different users to access some or all of the data while allowing for dynamic updates. Enabling dynamic data sharing in cloud storage while preserving users’ ability to search the data is crucial for promoting data flow and maximizing its value. This approach is particularly significant in addressing the data silo problem. However, existing security mechanisms remain imperfect, and most current scenarios assume that cloud servers are merely “curious but honest”. In reality, cloud servers may exhibit malicious behavior, such as returning incorrect or incomplete search results. Similarly, malicious users might falsify search results—for example, to avoid payment—or collude with cloud servers to steal other users’ search privacy. To address these challenges, this paper proposes an updatable multi-user dynamic searchable encryption scheme with bidirectional verification. The scheme enables secure dynamic data sharing in multi-user scenarios by constructing an index structure using homomorphic message authentication codes and bitmaps. This ensures secure updates to encrypted data without revealing the relationship between files and keyword search keys while providing forward and backward security. Regarding privilege management, the scheme employs updatable keys, ensuring that users can only generate valid search commands if they possess the latest encryption key. Additionally, blockchain technology is introduced to assist in verifying user honesty. Through actual testing and security analysis, the proposed solution demonstrates improved search speed over traditional methods while maintaining security. It also exhibits high adaptability for handling frequently changing cloud data. Full article

With the rapid increase in the number of vehicles and the growing demand for low-latency and reliable communication, traditional vehicular network architectures face numerous challenges. Unmanned Aerial Vehicle (UAV)-assisted vehicular networks provide an innovative solution for real-time data transmission and efficient cross-domain communication, significantly enhancing resource allocation efficiency and traffic safety. However, these networks also raise privacy and security concerns. Traditional symmetric key and Public Key Infrastructure (PKI)-based authentication schemes suffer from issues such as key management, certificate verification, and data leakage risks. While blockchain technology has been explored to address these problems, it still suffers from inefficiencies and high computational overhead. This paper proposes a UAV-assisted vehicular network architecture that leverages UAVs as trusted intermediaries for cross-domain authentication, effectively reducing authentication delays and improving scalability. Through ProVerif security proofs and detailed theoretical analysis, the proposed scheme is demonstrated to meet the security requirements of vehicular networks and withstand a broader range of attacks. Performance evaluation results show that the proposed scheme achieves at least a 20% reduction in computational and communication overhead compared to existing schemes, highlighting its significant advantages. Additionally, the average consensus time for the proposed scheme is at least 40% lower than existing schemes. The novelty of the proposed scheme lies in the integration of UAVs as trusted intermediaries with blockchain technology, addressing key management and privacy issues, and providing an efficient and secure solution for high-density vehicular networks. Full article

This research investigates the optimal integration of Blockchain Technology (BT) in Supply Chain Management (SCM) within Chile’s maritime ports. Utilizing fuzzy Logarithmic Methodology of Additive Weights (LMAW) and Double Normalization-based Multiple Aggregation Methods (DNMA), the study systematically identifies, prioritizes, and ranks key factors influencing BT adoption in SCM. The study’s findings highlight crucial factors like enhanced transaction security, good supply chain practices, and risk management. Furthermore, it ranks the application of ports as prime candidates for BT integration. The research contributes theoretically by developing a hybrid model combining MCDA methods, and practically by guiding the strategic application of BT in the maritime logistics sector, aligning with the principles of Industry 5.0. This paper presents a novel approach that explores the utilization of BT in maritime supply chain management, incorporating MCDA in a vague environment. The research gap of this study lies in defining new contexts in both theoretical and practical literature reviews for extending the use of BT in SCM in the ports of Chile, according to Industry 5.0, to increase the efficiency and effectiveness of all aspects of operations in these places. The contribution of this research is applying hybrid MCDA methods in an uncertain environment to assist decision-makers (DMs) in better implementing BT in SCM in Chilean ports, according to Industry 5.0. Full article

Nowadays, managers are facing the challenge of operating in situations of high uncertainty: delayed deliveries, lack of energy or rising energy and gas costs, the need to replace energy sources, and changing supply and sales markets. In the literature, two dominant trends in the activities of enterprises in the face of crises can be distinguished: (I) changes in supply chain management (increased flexibility by searching for local suppliers); and (II) transition to digital production and investment in technologies in the concept of Industry 4.0 or even Industry 5.0, such as artificial intelligence, 3D printing, robots, cyber-physical systems, digital manufacturing, and blockchain. A gap in the research has been observed in examining the impacts of these actions on the implementation of sustainable solutions and designating organizational changes in manufacturing. The main goal of this study is to review the literature using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) for data collection and, secondly, the methodology of Systematic Literature Review (SLR) and Mapping in Literature Reviews (MLR). Our literature review of the selected databases is based on 566 published articles in 2020–2022. The achieved results indicate the main organizational changes in the context of sustainable development in manufacturing, namely in the business management area (adopting Sustainable Project Management (SPM), Sustainable Supply Chain Management practices, Sustainable Supplier Selection (SSS), and Resilient Manufacturing Strategy (RMS)) and in the production area (adopting Internet of Things (IoT)-enabled Additive Manufacturing assists, simulation software, and Life Cycle Assessment. The findings of our study revealed key relationships between the adoption of fifth-generation industrial technologies and the sustainable development of manufacturing. Full article

The Metaverse allows the integration of physical and digital versions of users, processes, and environments where entities communicate, transact, and socialize. With the shift towards Extended Reality (XR) technologies, the Metaverse is envisioned to support a wide range of applicative verticals. It will support a seamless mix of physical and virtual worlds (realities) and, thus, will be a game changer for the Future Internet, built on the Semantic Web framework. The Metaverse will be ably assisted by the convergence of emerging wireless communication networks (such as Fifth-Generation and Beyond networks) or Sixth-Generation (6G) networks, Blockchain (BC), Web 3.0, Artificial Intelligence (AI), and Non-Fungible Tokens (NFTs). It has the potential for convergence in diverse industrial applications such as digital twins, telehealth care, connected vehicles, virtual education, social networks, and financial applications. Recent studies on the Metaverse have focused on explaining its key components, but a systematic study of the Metaverse in terms of industrial applications has not yet been performed. Owing to this gap, this survey presents the salient features and assistive Metaverse technologies. We discuss a high-level and generic Metaverse framework for modern industrial cyberspace and discuss the potential challenges and future directions of the Metaverse’s realization. A case study on Metaverse-assisted Real Estate Management (REM) is presented, where the Metaverse governs a Buyer–Broker–Seller (BBS) architecture for land registrations. We discuss the performance evaluation of the current land registration ecosystem in terms of cost evaluation, trust probability, and mining cost on the BC network. The obtained results show the viability of the Metaverse in REM setups. Full article

The objective of this article is to assist the reader in understanding the journey from traditional Supply Chain Management to Digital Supply Chain Management. It aims to augment the concept of Digital Supply Chain Management with blockchain technology and create an extensive literature review to assist in formulating the gaps and discovering the variables that contribute towards the efficiency of a Blockchain-Based Digital Supply Chain. Moreover, this article aims to validate the impact of specified parameters resulting in customer retention and market leadership for an organization. Digital technologies such as the Internet of Things, blockchain, etc., are disrupting the traditional ways of doing business and creating value propositions for customers. Supply Chain Management is a key business process for an organization that helps them compete in the market. Organizations have seized competition not as individual brands but as supply chains. Digital Supply Chain Management is the implementation of digital technologies to capture customer data at every interaction to create customer engagement strategies. This article provides an empirical analysis of parameters influencing a Blockchain-Augmented Digital Supply Chain resulting in customer retention and market leadership and shows how, through a Blockchain-Based Digital Supply Chain, the business objective of being a customer-centric organization is assisted with the customer data generated at each interaction that is enabled. Full article

Purpose: The recent development in logistics due to the dawn of Logistics 4.0 has made global logistics providers more dependent on intelligent technologies. In this era, these technologies assist in data collection and transmission of logistical data and pose many security and privacy threats in logistics management systems. The customer’s private information, which is shared among the logistics stakeholders for optimal operation, faces unauthorized access due to a lack of privacy. This, amongst others, is a critical problem that needs to be addressed with blockchain. Blockchain is a disruptive technology that is transforming different sectors, and it has the potential to provide a solution to the issues mentioned above, with its unique features such as immutability, transparency, and anonymity. Method: This study designed a blockchain-based logistics management architecture on a decentralized peer-2-peer network using Ethereum smart contracts. The proposed system deployed the Rivest–Shamir–Adleman (RSA) asymmetric encryption method to protect the logistics system from cyber-attacks and secure customers’ private information from unauthorized access. Findings: Furthermore, the security and privacy of the proposed system are evaluated based on the theorem. The proof shows that the system can provide security to the logistics system and privacy to customers’ private data. The performance evaluation is based on throughput and latency. It shows that the proposed system is better than the baseline system, and the comparatives analysis shows that the proposed system is more secure and efficient than the existing systems. Implication and Limitation: The proposed system offers a better solution to the security/privacy of the logistics management system and provides recommendations to key stakeholders involved in the logistics industry while adopting blockchain technology. Apart from the study’s methodological limitation, it is also limited by a lack of reference materials. Full article

In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and Blockchain technologies have quickly gained pace as a new study niche in numerous collegiate and industrial sectors, notably in the healthcare sector. Recent advancements in healthcare delivery have given many patients access to advanced personalized healthcare, which has improved their well-being. The subsequent phase in healthcare is to seamlessly consolidate these emerging technologies such as IoT-assisted wearable sensor devices, AI, and Blockchain collectively. Surprisingly, owing to the rapid use of smart wearable sensors, IoT and AI-enabled technology are shifting healthcare from a conventional hub-based system to a more personalized healthcare management system (HMS). However, implementing smart sensors, advanced IoT, AI, and Blockchain technologies synchronously in HMS remains a significant challenge. Prominent and reoccurring issues such as scarcity of cost-effective and accurate smart medical sensors, unstandardized IoT system architectures, heterogeneity of connected wearable devices, the multidimensionality of data generated, and high demand for interoperability are vivid problems affecting the advancement of HMS. Hence, this survey paper presents a detailed evaluation of the application of these emerging technologies (Smart Sensor, IoT, AI, Blockchain) in HMS to better understand the progress thus far. Specifically, current studies and findings on the deployment of these emerging technologies in healthcare are investigated, as well as key enabling factors, noteworthy use cases, and successful deployments. This survey also examined essential issues that are frequently encountered by IoT-assisted wearable sensor systems, AI, and Blockchain, as well as the critical concerns that must be addressed to enhance the application of these emerging technologies in the HMS. Full article

Wireless body area networks (WBANs) are a research area that supports patients with healthcare monitoring. In WBAN, the Internet of Things (IoT) is connected with WBAN for a smart/remote healthcare monitoring system in which various medical diseases are diagnosed. Quality of service (QoS), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%). Full article

The security and privacy of electronic health records (EHRs) have received considerable attention from healthcare workers and researchers. To ensure security, various encryption and decryption schemes as well as key management protocols have been developed. However, owing to sharing and scalability issues, additional security technologies have been proposed. Nonetheless, these technologies cause other problems, such as efficiency issues. Blockchain-based EHR management systems have been proposed to overcome computational overhead. However, because most blockchain systems are installed by outsourcing companies, EHRs may be leaked to the company. Hence, we herein propose a blockchain-based EHR management scheme with proxy re-encryption. In this scheme, we set a proxy server that re-encrypts the ciphertext between file servers, thereby solving EHR sharing issues. Furthermore, because the server is separated from the blockchain system, the outsourcing company cannot manipulate the server or access the records. In addition, the blockchain assists in access control by using smart contracts, thereby enabling secure and efficient EHR sharing. By performing security analysis, we prove that our proposed scheme solves the aforementioned security problems. In addition, we experimentally demonstrate the efficient operation of the proposed system. Full article