Burhan Ul Islam Khan, Khang Wen Goh, Megat F. Zuhairi, Rusnardi Rahmat Putra · 6 authors
Amidst the rising demands for data security across expansive networks, blockchain technology is witnessing an upsurge in its adoption, particularly within Internet of Things (IoT) applications, services, and smart cities. Blockchains offer an immutable property that bolsters security and aids in the structured management of distributed ledgers. Nevertheless, ensuring scalability remains a formidable challenge, especially within decentralized Ethereum systems. Current methods often fall short of offering tangible solutions, and the scrutiny of Ethereum-based cases reveals persistent deficiencies in addressing scalability issues due to inherent system complexities, dependency on resource-intensive consensus algorithms, lack of optimized storage solutions, and challenges in ensuring synchronous transaction validation across a decentralized network. This paper proposes a foundational scheme underpinned by a unique graph-based topology and hash bindings for nodes that join the system. The proposed scheme establishes an innovative indexing mechanism for all transactions and blocks within the IoT framework, ensuring optimal node accessibility. Transaction and block replications occur over the joining nodes' graphical structure, ensuring efficient subsequent retrieval. A standout feature of the proposed scheme is its ability to enable participating nodes to forgo retaining a complete ledger, making it non-reliant on individual node capabilities. Consequently, this facilitates a broader spectrum of nodes to participate in the consensus system, irrespective of their operational prowess. This study also offers a novel empirical model for Proof-of-Validation (PoV), which reduces computational intricacy and expedites the validation process in stark contrast to prevailing blockchain systems.
Abstract Plant diseases are considered as the major bottleneck for the farmers to monitor and diagnosis with the super intelligent methods. With the onset of Artificial Intelligence, Internet of Things(IoT), predicting the plant diseases in early stages has given the bright light of hope to farmers for boosting the productivity of agriculture in which increases the country’s economy. But the current advances in the IoT-AI-driven data gathers data from the agricultural fields and integrates the strong communication system for the early prediction and diagnosis process. Though these intelligent drive systems have several advantages, these procedure have been suffering from the varied security challenges which accelerates an outcry for a cognitive systems in the form of data breaches and privacy problems. The protection of patient data remains a significant concern due to the sensitivity and value of healthcare information, especially when transmitted over the Internet. This has heightened the demand for secure systems to safeguard against data breaches and privacy issues. Similarly, in agriculture, security challenges have been addressed using Web 3.0 and Blockchain technologies, which are favored for their immutable and decentralized features. This research proposes an advanced Web 3.0 Ensemble hybrid blockchain framework to enhance authentication security within the agricultural sector. To improve the authentication process further, chaotic maps are used to generate highly dynamic hashes during the creation of genesis blocks, ensuring that all data is securely stored in the recommended approach. The framework was tested on the Ethereum blockchain using Web 3.0, with Python 3.19 as the primary programming language for developing various interfaces. The security strength of the framework was thoroughly assessed using NIST standard tests, and its robustness was compared with other blockchain models. The results demonstrate that the proposed framework provides stronger defenses against various attacks and surpasses varied approaches in terms of complexity and robustness.
The preservation of the vaccine cold chain is crucial in order to ensure the proper preservation of vaccines throughout transport in a controlled environment. Maintaining the vaccine at suitable temperature and humidity levels during transportation will significantly significantly impacts vaccine effectiveness and quality. However, exposure to high temperature or improper conditions will result in vaccine degradation and public health concerns. Moreover, centralized real-time monitoring systems often suffer from issues related to integrity, transparency, availability, and single points of failure. This paper aims to transition data infrastructure from centralized to decentralized to enhance confidentiality, integrity, and availability (CIA). The proposed system, InoculLedger, employs IOTA and smart contracts to monitor and control environmental parameters, taking into account the vaccine's manufacturing process until the patient receives it. The system ensures transparency at every stage the vaccine undergoes and disseminates this information to all stakeholders, including the patient. The system utilizes IOTA for data infrastructure and employs smart contracts for data management. Additionally, the proposed system uses the Internet of Things (IoT) to monitor environmental parameters in real time.
Ikramullah Khan, Sudip Phuyal, Ricardo Correia, João C. Ferreira
Abstract Healthcare providers face critical challenges in managing and exchanging patient health and medical records. Traditional health and medical data management systems, which often include paper-based records and work as closed, isolated silos, have demonstrated limitations in terms of data usability, interoperability, and patient privacy. This translates into limitations not only for providers but also for the patients, healthcare professionals, and other participants of the health-care value chain, hindering potential innovations and efficiency gains. Distributed Ledger Technology (DLT), such as the blockchain, is emerging as a possible solution to challenges in data management and beyond across several operational and administrative processes in healthcare services. This paper begins with an extensive overview of the literature with an emphasis on DLT implementations and applications in the healthcare industry. We examine how DLT has been used in real-world initiatives across the healthcare domain, highlight notable initiatives, and outline potential improvements. This may result from its adoption, namely in areas such as healthcare data sharing and interoperability, verifiability, transparency, or patient privacy and control. Overall, some of DLT’s native capabilities, such as data immutability, sharing and reconciliation across parties with varying levels of trust, and user self-sovereignty may translate into solutions for several caveats of the current healthcare technological infrastructures, and contribute to improving healthcare outcomes by fostering innovations, enabling broader sharing of healthcare data, enhancing transparency over the use of data, equipping patients with greater control over their data, and enabling new or improved services and processes in healthcare.
The rise of the Internet of Things (IoT) has driven significant advancements across sectors such as urbanization, manufacturing, and healthcare, all of which are focused on enhancing quality of life and stimulating the global economy. This survey offers an in-depth analysis of the integration of blockchain technology with IoT, addressing aspects such as architectural alignment, applications, security, limitations, scalability, and latency. Moreover, this survey focuses on security, integration techniques, and future research directions. The primary contributions of this review include a taxonomy of security concerns specific to IoT, an analysis of integration methods, and insights into consensus mechanisms suitable for resource-constrained environments. These findings highlight the unique challenges and opportunities in IoT–blockchain integration, providing a foundation for advancing secure and scalable IoT applications. By exploring consensus mechanisms and resource-constrained deployments, this paper provides a framework for developing secure and efficient IoT applications utilizing blockchain technology and providing a basis for future research and practical applications. In addition, this survey investigates innovative trends, including AI-driven blockchain for IoT.
As mobile devices proliferate and mobile applications diversify, Mobile Edge Computing (MEC) has become widely adopted to efficiently allocate computing resources at the network edge and alleviate network congestion. In the MEC initial phase, the absence of vital information presents challenges in devising task-offloading policies, and identifying malicious devices responsible for providing inaccurate feedback is complex. To fill in such gaps, we introduce a consortium blockchain-enabledCommitteeVoting basedTaskOffloadingModel (CVTOM) to collaboratively formulate resource allocation policies and establish deterrence against malicious servers producing erroneous results intentionally. Different voting principle mechanisms of each committee member are first designed in a Blockchain-enabled system which helps to represent the system's resource status. Additionally, we propose a Multi-armed Bandits relatedThompsonSampling basedAdaptivePreferenceOptimization (TSAPO) algorithm for task-offloading policy, enhancing the timely identification of potent edge servers to improve computing resource utilization which first considers dynamic edge server space and parallel computing scenarios. The solid proof process greatly contributes to the theoretical analysis of the TSAPO. The simulation experiments demonstrate the delay and budget can be reduced by around 25% and 10% respectively, showcasing the superior performance of our approach.
Chalima Dimitra Nassar Kyriakidou, Iakovos Pittaras, Athanasia Maria Papathanasiou, George Xylomenos · 5 authors
Despite its rapid growth, the Internet of Things (IoT) still faces significant challenges related to interoperability, transparency and security. To address these issues, we propose the utilization of smart contract-based Digital Twins (DTs) "hosted" in the Hyperledger Fabric blockchain network, while leveraging the Web of Things paradigm for interoperability. Thus, our solution includes several notable features, such as decentralization, auditability and security. However, implementing DTs using Distributed Ledger Technologies (DLTs) introduces certain overheads. In this paper, we assess the feasibility and evaluate the performance of smart contract-based DTs using a set of Key Performance Indicators (KPIs). Our results demonstrate that, although DLT-induced overheads, such as latency, are present, they remain manageable for IoT use cases.
HealthCare 4.0 stands as a cutting-edge technology that integrates human-sourced data with communication systems to enable highly accurate clinical diagnostics and treatments. While sensor-based devices have simplified many aspects of daily life, these advancements also face significant security challenges, particularly in safeguarding patient information. In response, this research introduces a novel blockchain-based hybrid chaotic encryption and authentication for maintaining EHR transmissions aimed at robust and secure authentication within HealthCare 4.0. The complete framework incorporates the Infura Web API, using Python 3.19. To strengthen authentication security, modified Hippopotamus-evoked scroll maps are used to generate dynamic hashes in the genesis block formation, securing all EHR data in the proposed architecture. This entire framework was evaluated on the Ethereum Blockchain, leveraging Web 3.0, with Python 3.19 serving as the core programming environment for interface development. Security analysis was performed utilizing Burrows-Abadi-Needham (BAN) logic, while the framework's resilience was rigorously tested against NIST standards. Comparative testing highlights the model's superior defense capabilities against various attacks, surpassing other frameworks in complexity and robustness. The findings ultimately provide a comprehensive view of the optimized encryption scheme on blockchain technology and the future pathways for secure authentication frameworks in HealthCare 4.0.
Abdul Subhani Shaik, M. Mahima, Jajimoggala Sravanthi, Hassan Ali · 6 authors
Therefore, there is a need to formulate a predictive analytics approach to get increased regulatory compliance within blockchain supply chain management. The plan is to apply machine learning to determine probabilistic outcomes that can be used in attempting to identify future compliance concerns and trends derived from analysis of past blockchain transactions. The model also becomes aware of the patterns in the supply chain data and hence estimates regulatory changes before the noncompliance incidents happen. Besides, smart contracts that include machine learning aspects allow for the automatic execution of regulation adherence. The system includes other document check mechanisms which utilize a Technical feature of artificial intelligence to ascertain the validity of documentation in the supply chain. Furthermore, risk assessment algorithm fosters compliance regulation attention by highlighting key compliance risks within the supply chain. By so doing, the system has the capability to identify fraudulent transactions and policies in an effort to prevent them as well as meet set compliance levels. In conclusion, this forward-looking work provides a holistic framework on how predictive analytics can aid in the kind of decision-making required to strengthen the transformative power of blockchain supply chains in the areas of compliance, openness, and responsibility.
Sujit Biswas, Kashif Sharif, Zohaib Latif, Mohammed J. F. Alenazi · 6 authors
Abstract Smart device manufacturers rely on insights from smart home (SH) data to update their devices, and similarly, service providers use it for predictive maintenance. In terms of data security and privacy, combining distributed federated learning (FL) with blockchain technology is being considered to prevent single point failure and model poising attacks. However, adding blockchain to a FL environment can worsen blockchain's scaling issues and create regular service interruptions at SH. This article presents a scalable Blockchain‐based Privacy‐preserving Federated Learning (BPFL) architecture for an SH ecosystem that integrates blockchain and FL. BPFL can automate SHs' services and distribute machine learning (ML) operations to update IoT manufacturer models and scale service provider services. The architecture uses a local peer as a gateway to connect SHs to the blockchain network and safeguard user data, transactions, and ML operations. Blockchain facilitates ecosystem access management and learning. The Stanford Cars and an IoT dataset have been used as test bed experiments, taking into account the nature of data (i.e. images and numeric). The experiments show that ledger optimisation can boost scalability by 40–60% in BCN by reducing transaction overhead by 60%. Simultaneously, it increases learning capacity by 10% compared to baseline FL techniques.
BACKGROUND: The benefits of smart contracts (SCs) for sustainable health care are a relatively recent topic that has gathered attention given its relationship with trust and the advantages of decentralization, immutability, and traceability introduced in health care. Nevertheless, more studies need to explore the role of SCs in this sector based on the frameworks propounded in the literature that reflect business logic that has been customized, automatized, and prioritized, as well as system trust. This study addressed this lacuna. OBJECTIVE: This study aimed to provide a comprehensive understanding of SCs in health care based on reviewing the frameworks propounded in the literature. METHODS: A structured literature review was performed based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) principles. One database-Web of Science (WoS)-was selected to avoid bias generated by database differences and data wrangling. A quantitative assessment of the studies based on machine learning and data reduction methodologies was complemented with a qualitative, in-depth, detailed review of the frameworks propounded in the literature. RESULTS: A total of 70 studies, which constituted 18.7% (70/374) of the studies on this subject, met the selection criteria and were analyzed. A multiple correspondence analysis-with 74.44% of the inertia-produced 3 factors describing the advances in the topic. Two of them referred to the leading roles of SCs: (1) health care process enhancement and (2) assurance of patients' privacy protection. The first role included 6 themes, and the second one included 3 themes. The third factor encompassed the technical features that improve system efficiency. The in-depth review of these 3 factors and the identification of stakeholders allowed us to characterize the system trust in health care SCs. We assessed the risk of coverage bias, and good percentages of overlap were obtained-66% (49/74) of PubMed articles were also in WoS, and 88.3% (181/205) of WoS articles also appeared in Scopus. CONCLUSIONS: This comprehensive review allows us to understand the relevance of SCs and the potentiality of their use in patient-centric health care that considers more than technical aspects. It also provides insights for further research based on specific stakeholders, locations, and behaviors.
After the emergence of the Internet of Things (IoT), the way devices interact with each other changed, as it allowed automation and seamless communication in various fields. However, various challenges related to security and trust have emerged, hindering the widespread adoption of the IoT. Blockchain technology is considered the ideal solution to face these challenges because of its immutable and decentralized nature. This paper explores the potential of blockchain technology to address critical security and trust challenges within the rapidly growing IoT ecosystem. Through a systematic literature review, this study examines how blockchain’s decentralized, immutable, and transparent features contribute to enhancing security and trust in IoT networks. Key findings indicate that blockchain integration can prevent data manipulation, ensure robust identity management, and facilitate transparent, verifiable transactions, supporting both security and trust in IoT systems. These attributes not only improve IoT security but also promote sustainable practices by optimizing resource efficiency, reducing environmental impact, and enhancing resilience in systems like supply chain management and smart grids. Additionally, this study identifies open research challenges and suggests future directions for optimizing blockchain in IoT environments, focusing on scalability, energy-efficient consensus mechanisms, and efficient data processing.
Ahmad AA Alkhatib, Layla Albdor, Seraj Fayyad, Hussain Ali
The rapid expansion of Internet of Things (IoT) devices underscores the critical importance of robust security protocols, particularly in the realm of children's toys. This study introduces an innovative multi-factor authentication strategy integrating Quick Response (QR) codes with Blockchain technology to fortify the security of IoT toys designed for children. The primary objective is to safeguard young users against potential threats stemming from unauthorized access, thereby ensuring a secure interaction with IoT-enabled toys. By amalgamating authentication factors, including QR codes, the proposed approach establishes a multilayered security framework. Leveraging the inherent immutability and transparency of Blockchain, the system verifies the authenticity of IoT toys by scanning a unique QR code, thus mitigating risks associated with malwares and unauthorized access. The decentralization of Blockchain ensures no single point of failure, enhancing resilience against cyber threats. Extensive usability studies underscore the efficacy and practicality of the advanced multi-factor authentication solution, poised to elevate the safety standards of IoT toys in the digital age. This innovative approach not only bolsters security but also fosters trust among users, enabling seamless and worry-free interaction with IoT-enabled toys for children worldwide.
In the contemporary era, the global proliferation of Internet of Things (IoT) devices exceeds 15 billion, serving functions from wearables to smart grid monitoring. These devices frequently manage sensitive data, underscoring the need for secure and reliable IoT networks leveraging blockchain technology. A key innovation of this study is an approach to mitigate vulnerabilities that quantum computing poses to blockchain-based IoT systems, which existing cryptographic methods cannot effectively address. Quantum computers could exploit these weaknesses to compromise key-pair generation and extract private keys from transaction signatures. To overcome this, the research introduces an optimized implementation of the post-quantum digital signature algorithm Dilithium-5, ensuring blockchain security and quantum readiness. These transaction signatures are designed for low-power, cost-effective microcontrollers, such as the ESP32, making the solution accessible for a wide range of IoT devices. In addition, the study includes a case study involving a post-quantum safe portable device for measuring blood oxygen levels and heart rate, illustrating the practical benefits and effectiveness of the proposed solution in enhancing IoT security against quantum threats. The results demonstrate that the proposed approach ensures quantum-resistant security while maintaining performance efficiency, making it suitable for real-world IoT applications.
The convergence of blockchain technology with Internet of Things (IoT) security frameworks represents a significant advancement in addressing modern cybersecurity challenges. As IoT networks expand to encompass billions of connected devices, traditional centralized security approaches prove increasingly inadequate in managing the scale, complexity, and heterogeneity of these systems. This paper provides a comprehensive analysis of blockchain-IoT integration, examining how distributed ledger technology can enhance IoT security through immutable device identity, decentralized architecture, and automated policy enforcement. Through extensive literature review spanning recent research and implementations, we investigate both the transformative potential and significant implementation challenges, including standardization issues, resource constraints, and privacy concerns. The research also explores emerging solutions and future directions, particularly in consensus mechanism optimization, hybrid architectures, and the integration of edge computing. Our findings indicate that while blockchain technology offers promising solutions for critical IoT security requirements, successful implementation demands careful consideration of resource limitations, scalability needs, and standardization efforts.