James Kolapo Oladele, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Frances Uchechukwu Emordi · 8 authors
Blockchain platforms propagate into every facet, including managing medical services with professional and patient-centered applications. With its sensitive nature, record privacy has become imminent with medical services for patient diagnosis and treatments. The nature of medical records has continued to necessitate their availability, reachability, accessibility, security, mobility, and confidentiality. Challenges to these include authorized transfer of patient records on referral, security across platforms, content diversity, platform interoperability, etc. These, are today – demystified with blockchain-based apps, which proffers platform/application services to achieve data features associated with the nature of the records. We use a permissioned-blockchain for healthcare record management. Our choice of permission mode with a hyper-fabric ledger that uses a world-state on a peer-to-peer chain – is that its smart contracts do not require a complex algorithm to yield controlled transparency for users. Its actors include patients, practitioners, and health-related officers as users to create, retrieve, and store patient medical records and aid interoperability. With a population of 500, the system yields a transaction (query and https) response time of 0.56 seconds and 0.42 seconds, respectively. To cater to platform scalability and accessibility, the system yielded 0.78 seconds and 063 seconds, respectively, for 2500 users.
The implementation of blockchain technology in integrated IoT networks for constructing scalable Intelligent Transportation Systems (ITS) in India has the potential to revolutionize the way we approach transportation. By leveraging the power of IoT and blockchain, we can create a highly secure, transparent, and efficient system that can transform the way we move people and goods. India, one of the world's most populous countries, has a highly congested and inefficient transportation system that often leads to delays, accidents, and waste of time and resources. The integration of IoT and blockchain can help address these issues by enabling real-time monitoring, tracking, and optimization of traffic flows, thereby reducing congestion, improving safety, and increasing the overall efficiency of the transportation system. This paper explores the potential of blockchain technology in the context of integrated IoT networks for constructing scalable ITS systems in India. The methodology followed is to develop a proof-of-concept blockchain-based application for ITS, Implement the blockchain solution into the existing ITS infrastructure, and ensure proper integration and compatibility with other systems. Conduct thorough research and maintenance to ensure the reliability and sustainability of such blockchain-based systems. Research discusses the various benefits and challenges of this approach and the various applications of this technology in the transportation sector, including the Green Sustainability concept. Results find various ways in which such implementations of blockchain and IoT-ML can revolutionize transportation systems.
Federated learning (FL) has shown promise in smart industries as a means of training machine-learning models while preserving privacy. However, it contradicts FL’s low communication latency requirement to rely on the cloud to transmit information with data owners in model training tasks. Furthermore, data owners may not be willing to contribute their resources for free. To address this, we propose a single contract to dual contract approach to incentivize both model owners and workers to participate in FL-based machine learning tasks. The single-contract incentivizes model owners to contribute their model parameters, and the dual contract incentivizes workers to use their latest data to participate in the training task. The latest data draw out the trade-off between data quantity and data update frequency. Performance evaluation shows that our dual contract satisfies different preferences for data quantity and update frequency, and validates that the proposed incentive mechanism is incentive compatible and flexible.
Integrating sharded blockchain with IoT presents a solution for trust issues and optimized data flow. Sharding boosts blockchain scalability by dividing its nodes into parallel shards, yet it's vulnerable to the $1\%$ attacks where dishonest nodes target a shard to corrupt the entire blockchain. Balancing security with scalability is pivotal for such systems. Deep Reinforcement Learning (DRL) adeptly handles dynamic, complex systems and multi-dimensional optimization. This paper introduces a Trust-based and DRL-driven (\textsc{TbDd}) framework, crafted to counter shard collusion risks and dynamically adjust node allocation, enhancing throughput while maintaining network security. With a comprehensive trust evaluation mechanism, \textsc{TbDd} discerns node types and performs targeted resharding against potential threats. The model maximizes tolerance for dishonest nodes, optimizes node movement frequency, ensures even node distribution in shards, and balances sharding risks. Rigorous evaluations prove \textsc{TbDd}'s superiority over conventional random-, community-, and trust-based sharding methods in shard risk equilibrium and reducing cross-shard transactions.
Sharding technology can address the throughput and scalability limitations that arise when single-chain blockchain are applied in the Internet of Things (IoT). However, existing sharding solutions focus on addressing issues like malicious nodes clustering and cross-shard transactions. Existing sharding solutions cannot adapt to the performance disparities of edge nodes and the characteristic of three-dimensional data queries in building IoT. This leads to problems such as shard overheating and inefficient data query efficiency. This paper proposes a dual-layer architecture called S-DAG, which combines sharded blockchain and DAG blockchain. The sharded blockchain processes transactions within the building IoT, while the DAG blockchain stores block headers from the sharded network. By designing an Adaptive Balancing Load Algorithm (ABLA) for periodic network sharding, nodes are divided based on their load performance values to prevent the aggregation of low-load performance nodes and the resulting issue of shard overheating. By combining the characteristics of the KD tree and Merkle tree, a block structure known as 3D-Merkle tree is designed to support three-dimensional data queries, enhancing the efficiency of three-dimensional data queries in building IoT. By deploying and conducting simulation experiments on various physical devices, we have verified the effectiveness of the solution proposed in this paper. The results indicate that, compared to other solutions, the proposed solution is better suited for building IoT data management. ABLA is effective in preventing shard overheating issue, and the 3D-Merkle tree significantly enhances data query efficiency.
Fatemeh Stodt, Mohammed B. Alshawki, Christoph Reich, Fabrice Théoleyre · 5 authors
In the rapidly evolving realm of the Industrial Internet of Things (IIoT), securing shop floor operations, especially in audit processes, is of critical importance. This paper confronts the challenge of ensuring data integrity and trust in IIoT systems by leveraging the capabilities of blockchain technology. The unique characteristics of blockchain, such as its immutable and decentralized ledger, establish a solid and transparent foundation for verifying shop floor transactions and activities. We introduce a privacy-centric approach, meticulously designed to comply with stringent data privacy regulations. This method allows auditors to authenticate both IIoT data and devices, ensuring confidentiality and adhering to regulatory standards. Our practical implementation strategy, tailored for shop floor environments, not only enhances the security of device and data integrity but also showcases robustness against specific adversarial threats, including network intrusion, data tampering, and unauthorized access. The findings indicate that our approach not only amplifies security protocols but also integrates effortlessly with existing IIoT infrastructures. It presents an efficient, scalable solution that elevates the safety and reliability of IIoT ecosystems, making it a significant step forward in the quest for secure and compliant industrial operations.
Online social networks (OSN) that gather diverse interests have attracted a vast user base. However, centralized online social networks, which house vast amounts of personal data, are plagued by issues such as user privacy and data breaches, tampering, and single points of failure. The centralization of social networks results in sensitive user information being stored in a single location, making data breaches and leaks capable of simultaneously affecting millions of users who rely on these platforms. Therefore, research into decentralized social networks is crucial. However, blockchain-based social networks present challenges related to resource limitations. This paper proposes a reliable and scalable online social network platform based on blockchain technology. This system ensures the integrity of all content within the social network through the use of blockchain, thereby preventing the risk of breaches and tampering. Through the design of smart contracts and a distributed notification service, it also addresses single points of failure and ensures user privacy by maintaining anonymity. Furthermore, it tackles the scalability concerns associated with blockchain-based systems due to excessive computing resource utilization by improving the off-chain storage structure. By adopting Bloom filters and off-chain storage, it effectively alleviates the burden on on-chain storage. Comparative analysis with related studies demonstrates a minimum of 74% cost savings during post uploads. While the proposed system exhibits slightly slower write performance by 10% compared to existing systems, it showcases 13% faster read performance and achieves an average notification latency of 3 seconds. Thus, this system addresses scalability issues present in blockchain-based systems. It offers a solution that enhances data management not only for online social networks but also for resource-constrained system of blockchain-based IoT environments. By applying this system, data can be managed securely and efficiently.
Cognitive Radio Ad-hoc Networks (CRAHNs) are under constant attacks from compromised primary & secondary nodes. These attacks focus on bandwidth manipulation, internal configuration manipulation, and selective spoofing, which can disturb the normal working of the CRAHNs. Researchers propose various security models to mitigate these attacks, each with limitations. Most of these models have higher complexity, while others cannot be used to mitigate multiple attack types. To overcome these issues while maintaining higher security and Quality of Service (QoS) under attacks, this text proposes a design of a novel blockchain-based security model for improving attack resilience in CRAHNs. The model initially collects multiple information sets from different cognitive radio controllers and creates active & redundant miners for the storage of these sets. The number of active & redundant miners is decided via a Mayfly Optimizer (MO) Model, which assists in improving resource utilization while reducing deployment costs. Cognitive rules and configurations are stored on these nodes and updated via a secure blockchain verification. Due to this, the proposed model demonstrated significant improvements in cognitive radio communications across various metrics, even under different attack scenarios. It reduced communication delay by up to 18.5%, increased communication throughput by up to 19.5%, and improved the Packet Delivery Ratio (PDR) by up to 19.4% when compared with existing models such as SRC [2], Prob Less [4], and DDQL [13]. Additionally, the model achieved energy savings of up to 12.5%. These enhancements were made possible by the optimized selection of miner nodes, enabling quicker mining for high-speed communication, low-energy mining tasks for prolonged use, and high-performance mining for consistency. The results affirm the model’s suitability for various real-time cognitive radio scenarios. Due to the integration of the MO Model, the CRAHN showcases better communication speed, lower energy consumption, higher throughput, and higher packet delivery performance when compared with existing methods under real-time scenarios.
As a result of the ubiquitous network applications and services, exacerbated by the overarching digital revolution the need and demand for efficient and dependable connectivity solutions have surged to unprecedented levels. Quality of Service (QoS)-based routing has emerged as a critical solution, enabling service differentiation, efficient resource allocation, and improved network performance. In this study, we introduce a novel Genetic Algorithm-powered QoS-aware Cross-Network Traffic Engineering framework,GATE-BC, at the confluence of Software Defined Networking (SDN) and Blockchain (BC) technologies.GATE-BCorchestrates end-to-end (E2E) QoS traffic, providing resource-efficient, reliable, and latency-tolerant delivery of intelligent network services in BC-enabled SDNs. Leveraging BC features such as decentralization, transparency, and immutability,GATE-BCeliminates the need for centralized entities in QoS-supported cross-network routing models. We compareGATE-BCframework with three other traffic management and engineering approaches: QoSChain (QC), Hierarchical Routing Approach (HRA), and Distributed Routing Approach (DRA). The extensive simulations reveal thatGATE-BCoutperforms the other routing strategies in terms of Path Setup Time (PST), Network Message Overhead (NMO), Request Acceptance Ratio (RAR), Network Bandwidth Consumption (NBC), Average Path Length (APL), and Average Network Length (ANL) metrics under various network topologies. Furthermore,GATE-BCemploys three different feasible path selection strategies based on bandwidth (GATE-BC_BW), delay (GATE-BC_D), and reliability (GATE-BC_R) QoS parameters to satisfy the service levels requested.
The advancements in telecommunications are significantly benefiting the Internet of Vehicles (IoV) in various ways. Minimal latency, faster data transfer, and reduced costs are transforming the landscape of IoV. While these advantages accompany the latest improvements, they also expand cyberspace, leading to security and privacy concerns. Vehicles rely on trusted authorities for registration and authentication processes, resulting in bottleneck issues and communication delays. Moreover, the central trusted authority and intermediate nodes raise doubts regarding transparency, traceability, and anonymity. This paper proposes a novel vehicle authentication handover framework leveraging blockchain, IPFS, and hybrid computing. The framework uses a Proof of Reputation (PoR) consensus mechanism to improve transparency and traceability and the Elliptic Curve Cryptography (ECC) cryptosystem to reduce computational delays. The suggested system assures data availability, secrecy, and integrity while maintaining minimal latency throughout the vehicle re-authentication. Performance evaluations show the system’s scalability, with creating keys, encoding, decoding, and registration operations done rapidly. Simulation is performed using SUMO to handle vehicle mobility in an IoV environment. The findings demonstrate the practicality of the proposed framework in vehicular networks, providing a reliable and trustworthy approach for IoV communication.
Patikiri Arachchige Don Shehan Nilmantha Wijesekara
Load Balancing (LB) in networking attempts to minimize the under-utilization and over-utilization of network resources by distributing the network flows evenly in the communication network. Blockchain includes a string of joined blocks that are built into the preservation of the non-tampering nature and safeguarding the verifiability. According to our felt experience, we are the initiators to review on blockchain-driven LB, where we organize the blockchain-driven LB concept under 7 categories and interpret thoroughly their performance in relation to LB techniques, BC-driven variables, LB approach, network variables, and similar things. We accumulated an early sample of 76 paper citations by handpicking articles for eligibility requirements scrutinized from web repositories, deploying a thorough and continuous method. Relying on this assessment, blockchain has been deployed in network LB for protecting data fidelity, trustworthiness, confidentiality of data transfers, deploying blockchain consensus for LB, deploying smart contracts for LB, deploying with secure resource trading, access control, and as a coordinator in the system of LB. Moreover, LB involves balancing loads in the blockchain transactions themselves. Thorough interpretation depicts that from blockchaindriven LB schemes, 37.5% deploy blockchain transaction LB, 90% deploy conventional blockchain architecture, 30% deploy generic consensus, 97.5% deploy decentralized LB, 97.5% deploy dynamic LB, 52.5% deploy deterministic LB, and the majority target generic networks. Finally, we go over the potential and predicaments of the notion of blockchain-driven LB and then provision ideas to defeat them.
Electronic Health Records (EHRs) have become an increasingly significant source of information for healthcare professionals and researchers. Two technical challenges are addressed: motivating federated learning members to contribute their time and effort, and ensuring accurate aggregation of the global model by the centralized federated learning server. To overcome these issues and establish a decentralized solution, the integration of blockchain and federated learning proves effective, offering enhanced security and privacy for smart healthcare. The proposed approach includes a gamified element to incentivize and recognize contributions from federated learning members. This research work offers a solution involving resource management within the Internet of Medical Things (IoMT) using a newly proposed trust decentralized loop federated learning consensus blockchain. The obtained raw data is pre-processed by using handling missing values and adaptive min-max normalization. The appropriate features are selected with the aid of hybrid weighted-leader exponential distribution optimization algorithm. Because, data with multiple features exhibits varying levels of variation across each feature. The selected features are then forwarded to the training phase through the proposed pyramid squeeze attention generative adversarial networks to classify the EHR as positive and negative. The proposed classification model demonstrates high flexibility and scalability, making it applicable to a wide range of network architectures for various computer vision tasks. The introduced model provides better outcomes in terms of 98.5% in the training accuracy and 99% in the validation accuracy over Medical Information Mart for Intensive Care III (MIMIC-III) dataset, which is more efficient than the other traditional methods.
The main aim of the proposed system is to facilitate secure and protected land registry in the domain of agriculture Industry 5.0. Considering the outlook of issues associated with it, we considered the blockchain and AI-based technology to fulfill the purpose of secure land registry. Establishing and confirming land ownership is essential for the land registry system in ensuring the protection of ownership rights, particularly crucial in the contexts of agriculture and Industry 5.0. In these sectors, land serves as a crucial resource for sustainable development and industrial innovation. Most of the existing works rely on legacy and centralized system to store land records; which result in high incidences of forgery and fraud. Therefore, maintaining a robust land registry system is essential to fostering economic investments, promoting green practices, and facilitating equitable access to land resources in agriculture and Industry 5.0 ecosystem. We proposed an AI and blockchain-enabled land registry system for agriculture and industry 5.0 that offers a more reliable, transparent, and efficient solution to the challenges of lack of transparency, data tampering, and inefficiency, which can result in disputes, fraudulent claims, and a lack of trust during the land registry. AI models, such as logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGB), and light gradient boosting machine (LGBM), are employed to classify the fraud and non-fraud land data. Only the non-fraud land data is forwarded into the blockchain network, thereby reducing the computational overhead of the proposed land registry system. In the blockchain network, we designed various smart contracts that validate the land data with unparalleled efficiency and security. Further, the slither solidity source analyzer tool is used for smart contract vulnerability assessment. After the assessment, the smart contract is deployed using the Sepolia test network. The non-fraudulent land data is redirected to the interplanetary file system (IPFS) that stores the original data and forwards the associated hash into the blockchain’s immutable ledger. The entire proposed system is evaluated with different performance parameters, such as AI statistical measures including accuracy, ROC, log-loss score, blockchain scalability comparison, gas cost utilization, and bandwidth utilization. Furthermore, the vulnerability assessment of the smart contract is analyzed using Slither to highlight the working of proposed system without any vulnerabilities. The proposed blockchain and AI-based land registry system ensure a secure and intelligent pipeline to combat against land forgery activities.
Badiea Abdulkarem Mohammed, Mahmood A. Al-Shareeda, Abeer Abdullah Alsadhan, Zeyad Ghaleb Al-Mekhlafi · 8 authors
The driving experience in fifth-generation (5G)-assisted vehicular fog computing systems has improved thanks to recent advancements in intelligent transportation. However, in the present vehicular system setup, the phenomenon of providing low computation overhead with massive serving capability is crucial. In the existing scenario, the computational complexity rises when an authenticated driver travels from one roadside unit (RSU) area to another RSU region and must undergo re-authentication by the existing RSU. In this paper, an efficient blockchain-based pseudonym authentication scheme to address these issues and avoiding using RSU for 5G-assisted vehicular fog computing. The pseudonym identity generated for each vehicles and fog servers in order to exchange information about the road environment. The proposed scheme avoids re-authentication by the future fog server by utilising bilinear pairing of points on the elliptic curve and utilising blockchain technology without the need for a trusted authority. For fog computing, fog server obtains the verification key to authenticate the messages sent from vehicles for supporting revocation. The security analysis part of this work shows that the proposed scheme is not only satisfy requirements of security and privacy, but also resistance security attacks. Finally, the evaluation of the proposed scheme’s performance shows that it is more efficient than existing schemes with regards to computation cost, verification speed, and energy consumption.
Claudia Pipino, Gaetano Rocco, Claudio Pagano, Andrea Cipriano
Small and Midsize Enterprises (SMEs) have faced innovative changes in their organizational structure, especially in human resources (HR) and employee management: these digital structural changes have transformed their business practices and strategies. The employees with new technical skills have also been impactful in this digitalization. The HR departments in SMEs have become increasingly pivotal in recruiting new employees and supporting existing employees throughout the organization. ITSvil in Salerno (Italy) has developed the Easywork project based on the “Fenice” microservices architecture. This system supports the HR departments in efficiently managing HR activities through digitalization. The first step in acquiring new resources is formulating the employment contract, which is essential for stipulating agreements on specific job requirements. Blockchain technology and smart contracts are among recent technological innovations impacting this process. Writing contracts in digital codes to simplify and effectively manage the legal relationship involving bureaucratic tasks and cost management is now possible. The new digital system makes employment contract processing transparent, traceable, and reliable. This research presents the design and development of a new microservice compatible and integrable process with the “Fenice” system based on blockchain technology. The proposed digital system aims to make HR management activities more transparent and traceable.
As the modern computing market experiences a surge in demand for efficient data-management solutions, challenges posed by centralized storage systems become more pronounced, especially with the proliferation of Internet of Things devices. Centralized storage, although cost-effective, faces issues of scalability, performance bottlenecks, and security vulnerabilities. With decentralized storage, data are distributed across nodes, offering redundancy, data availability, and enhanced security. Unfortunately, decentralized storage introduces its own challenges, such as complex data retrieval processes, potential inconsistencies in data versions, and difficulties in ensuring data privacy and integrity in a distributed setup. Effectively managing these challenges calls for innovative techniques. In response, this paper introduces a decentralized storage system that melds cloud-native concepts with blockchain technology. The proposed design delivers enhanced scalability, data security, and privacy. When operating on a containerized edge infrastructure, this storage system provides higher data-transfer speeds than the interplanetary file system. This research thus blends the advantages of cloud-native frameworks with the security mechanisms of blockchain, crafting a storage system that addresses the present-day challenges of data management in decentralized settings.
The thriving Internet of Things, a paradigm shift from the traditional Internet has brought about great societal improvements such as smart homes, smart cities, smart health, intelligent systems and many more. With these diverse societal improvements come increasing complexities in the areas of system efficiency, privacy, and security. In recent years ample academic and industrial research have delved into resource optimization to the detriment of security, as security features are left to be bolted on at the end of design and developmental processes. This approach leaves the system susceptible to threats and attacks. Consequently, this paper seeks to incorporate security features from the onset, weaving the security feature into the system's design and developmental phase. The proposed model structured in a three-tiered design comprises of concepts of Blockchain, edge computing, clustering techniques and a hybrid algorithm consisting of the static round-robin and the dynamic resource-based algorithms. The composition of the structural layout which considers aspects of the blockchain as a security tight measure for resource optimization in Internet of Things' environment, also incorporates features of edge computing, clustering techniques and the hybrid algorithm as components for resource optimization of the Internet of Things. In addition to the prospective security feature provided by the Hyperledger fabric BC in the proposed model, simulation results illustrate the Hyperledger fabric BC's dexterity in making IoT systems even more efficient, further showing its efficacy over the PSOR2B and the BC-EDSSP.
Blockchain technology has become a pivotal asset in many industries, particularly Food Supply Chain Management. This technology, renowned for its capacity to preserve data immutably and expedite tracking across the intricate stages of the food supply chain, plays a pivotal role in enhancing transparency across the food industry. We proposed a Blockchain-based Federated Learning model. This model amalgamates the strengths of Blockchain and federated learning within the food supply chain, focusing on sustainable and high-quality food production. Our primary objective is to fortify data security within various facets of the food supply chain, encompassing raw material suppliers, producers, distributors, and consumers. Simultaneously, we strive to enhance the precision of our model, aiming to outperform existing Blockchain-based solutions in terms of accuracy. The proposed model demonstrates superior accuracy compared to existing methods.
Muna Elsadig, Manal Abdullah Alohali, Ashraf Osman Ibrahim, Anas W. Abulfaraj
The Metaverse platform offers 3D immersive experiences through virtual reality, artificial intelligence, and blockchain technologies. Blockchain-based Metaverse has garnered recent interest due to its decentralization, anonymity, and other security features. Integrating blockchain into Metaverse promotes the formation of a shared ecosystem and provides digital asset tracking, privacy protection, and security in both virtual and physical environments. This paper explores the role of blockchain in creating and managing the Metaverse platform. It is intended to provide a helpful reference for researchers and practitioners in the field of the blockchain-based Metaverse. The main topics covered include the concept and characteristics of the Metaverse; its different use cases, architectures, and technologies; Metaverse as a service provider; Metaverse management; Metaverse users and data; and blockchain-based Metaverse in terms of roles, technologies, applications, and challenges. In addition, recent advances in the blockchain-based Metaverse and challenges such as scalability, interoperability, and edge resource sharing will be discussed. The paper will conclude by highlighting open research issues and future directions, including improving immersion, scalability, security, and integration with existing systems.
Sharding technology is widely regarded as an effective way to solve blockchain scalability limitations, such as lower throughput and longer delay time. However, sharding encounters challenges related to high cross-shard transactions proportion and complex cross-shard transaction verification. Therefore, a transaction sharding algorithm based on account-weighted graph is proposed. Firstly, an account-based transaction sharding model is established from the viewpoint of data sharding. Secondly, based on this model, an account-weighted graph is constructed with accounts as nodes and transaction frequency between accounts as weights for the long-term accumulated transaction data of blockchain. The community discovery algorithm is adopted, and the accounts with the largest modularity gain are selected and merged according to the association relationship between the accounts, so multi-shards blockchain is formed initially. Finally, multi-shards blockchain are adjusted and rebuilt by splitting and merging. The proposed algorithm is compared with modular sharding algorithm and random sharding algorithm under the sharding size of 10. The cross-shard transaction proportion is reduced by 78%, the average cross-shard transaction delay of accounts is reduced by 36.1% and 44.5%, and the transaction throughput is increased by 93% and 122%. Under the other granularities, the proposed algorithm also outperforms the two algorithms in terms of cross-shard transaction proportion and account transaction delay. In conclusion, the method effectively reduces the cross-shard transaction proportion and minimizes cross-shard transaction delay.
Wireless body area networks (WBAN) are essential components of intelligent healthcare monitoring techniques. Especially, when the number and datatype inWBANincreases. InWBAN, secure multidimensional data aggregation received a lot of attention. However, the related schemes consume more computational and communication overhead to encrypt/decrypt the multidimensional health reports. In this paper, a blockchain-assisted scalable and secure multidimensional data aggregation scheme is introduced for fog-basedWBAN. The multidimensional health data are efficiently generated, encrypted, and decrypted by using the Paillier cryptosystem. Further, the batch verification method is used to achieve efficient authentication. The proposed system offers significant security attributes with less computation and communication overhead in comparison with competing systems. Further, it supports statistical analyses such as summation and variance to analyze the received health report.
Electronic health records (EHRs) represent an innovative approach to constructing a distributed data analysis framework for managing health data within its original location. The integration of blockchain technology into EHR systems offers substantial improvements in security, privacy, and transparency, thus enhancing overall management efficiency. Our research spanned from January 2017 to December 2022, conducting a meticulous systematic literature review across reputable databases such as Scopus, IEEE Xplore, Springer, PubMed Central, and ScienceDirect. This comprehensive search, finalized in December 2022, utilized stringent inclusion and exclusion criteria to ensure the selection of high‐quality articles, thereby guaranteeing transparency and unbiased results. Through this systematic review, our primary objective was to explore, assess, and analyze the diverse architectures, proposed models, limitations, and future trajectories of blockchain‐enabled EHR systems. Our emphasis was on highlighting blockchain’s adaptability and robustness in healthcare contexts while identifying potential challenges and areas for further investigation. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis guidelines, we scrutinized more than 600 scientific studies, culminating in the selection of 31 articles that met our rigorous inclusion standards. Our technical and architectural evaluations delved into critical aspects such as privacy, security, authentication, availability, data control, storage, and resource consumption. Our research outcomes underscore the effective resolution of security, privacy, and availability concerns in EHRs through blockchain integration. However, we observed potential trade‐offs, including impacts on performance, resource utilization, and regulatory compliance. To address these complexities, we introduce an integrated framework designed to mitigate key challenges and deliver substantial value within this domain.
Muhammad Usman, Muhammad Shahzad Sarfraz, Muhammad Umar Aftab, Usman Habib · 5 authors
Industrial Internet of Things (IIoT) applications consist of resource constrained interconnected devices that make them vulnerable to data leak and integrity violation challenges. The mobility, dynamism, and complex structure of the network further make this issue more challenging. To control the information flow in such environments, access control is critical to make collaboration and communication safe. To deal with these challenges, recent studies employ attribute-based access control on top of blockchain technology. However, the attribute-based access control frameworks suffer due to high computational overhead. In this paper, we propose an improved role-based access control framework using hyperledger blockchain to deal with IIoT requirements with less computational overhead making the information control process more efficient and real-time. The proposed framework leverages a layered architecture of chaincodes to implement the improved access control framework that handles the permission delegation and conflict management to deal with the dynamism of the IIoT network. The system uses a Policy Contract, Device Contract, and Access Contract to manage the workflow of the whole access control process. Each chaincode in the proposed framework is isolated in terms of its responsibilities to make the design low coupled. The integration of improved access control with blockchain enables the proposed framework to provide a highly scalable solution, tamper-proof, and flexible to manage conflicting scenarios. The proposed system outperforms the recent studies significantly in computational overhead in extensive simulation results. To verify the scalability and efficiency, the proposed is evaluated against a large number of concurrent virtual clients in simulation and statistical analysis proves that the proposed system is promising for further research in this domain.
In the field of vehicular communication, the Internet of Vehicles (IoV) serves as a new era that guarantees increased connectivity, efficiency, and safety. The modern area and new technology have their challenges and constraints, though. This paper thoroughly examines these constraints significantly; we show how blockchain technology is being used to overcome them. This paper primarily explores the complexities of Blockchain-enabled Internet of Vehicles (BIoV) architectures, the applications they serve, and the robust security features they provide through a systematic literature review (SLR). In addition, we look at the several ways that blockchain and IoV might be integrated and investigate the subtle factors that should be considered when choosing consensus algorithms to maximize performance on different blockchains. This paper also addresses the methods and tools used to identify and avoid fraudulent activities in BIoV networks at a maximum level of security. It also reveals the wide range of BIoV applications and analyzes the different security levels they provide. In closing, we give an idea of the possibilities that will continue to develop the blockchain and IoV environment, reducing the roadblocks and advancing this combination toward a more secure, effective, and connected future for vehicle communication systems.