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Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentralized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, careful ma...
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... framework automatically categorizes sensitive health data for MH(Migration Handler) because tasks on the sensitive data is considered to be sensitive. The framework depicted in Figure 6 has two kinds of the rule-based classifier. The data and metadata containing task information are fed into the first rule-based classifier. ...
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... smartphone transmits two kinds of tasks: lightweight(5-10KB) and heavyweight tasks(5-10MB) to the embedded Fog Agents. The effect of task's data size on execution time and energy consumption is shown in figure 16(a) and 16(b). Migrating lightweight tasks needs less energy consumption than that of heavyweight tasks. ...
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... However, eHealth services have not developed as much as anticipated, partly due to issues of dependability, fault tolerance, and privacy. In eHealth, biological data collected by IoT devices is transmitted to Cloud entities operated by third parties, which presents challenges for data security and the protection of a patient's privacy [8][9][10][11][12]. ...
... In the article [11], the authors suggest a Blockchainenabled decentralized electronic healthcare architecture that is composed of three layers: 1) The Sensing layer, which consists of several medical sensors that are often placed on or inside a patient's body and transfer data to a smartphone. 2) The Edge Networks are made up of devices that are close to the data-detecting IoT devices. ...
Blockchain technologies (BCT) are utilized in healthcare to facilitate a smart and secure transmission of patient data. BCT solutions, however, are unable to store data produced by IoT devices in smart healthcare applications because these applications need a quick consensus process, meticulous key management, and enhanced eprivacy standards. In this work, a smart and secure eHealth framework SSEHCET (Smart and Secure EHealth Framework using Cutting-edge Technologies) is proposed that leverages the potentials of modern cutting-edge technologies (IoT, 5G, mobile edge computing, and BCT), which comprises six layers: 1) The sensing layer-WBAN consists of medical sensors that normally are on or within the bodies of patients and communicate data to smartphones. 2) The edge layer consists of elements that are near IoT devices to collect data. 3) The Communication layer leverages the potential of 5G technology to transmit patients' data between multiple layers efficiently. 4) The storage layer consists of cloud servers or other powerful computers. 5) Security layer, which uses BCT to transmit and store patients' data securely. 6) The healthcare community layer includes healthcare professionals and institutions. For the processing of medical data and to guarantee dependable, safe, and private communication, a Smart Agent (SA) program was duplicated on all layers. The SA leverages the potential of BCT to protect patients' privacy when outsourcing data. The contribution is substantiated through a meticulous evaluation, encompassing security, ease of use, user satisfaction, and SSEHCET structure. Results from an in-depth case study with a prominent healthcare provider underscore SSEHCET's exceptional performance, showcasing its pivotal role in advancing the security, usability, and user satisfaction paradigm in modern eHealth landscapes.
... Transactions are also expensive, and thus an attacker is less likely to spend money by sending several transactions. Blockchain technologies such as Ethereum also have transaction fees that depend on the size of the transaction packets that are sent [43]. In summary, these security requirements is rooted in a thorough understanding of potential vulnerabilities and the strategic application of measures to address them. ...
The Internet of Things (IoT) has recently attracted much interest from researchers due to its diverse IoT applications. However, IoT systems encounter additional security and privacy threats. Developing an efficient IoT system is challenging because of its sophisticated network topology. Effective access control is required to ensure user privacy in the Internet of Things. Traditional access control methods are inappropriate for IoT systems because most conventional access control approaches are designed for centralized systems. This paper proposes a decentralized access control framework based on smart contracts with three parts: initialization, an access control protocol, and an inspection. Smart contracts are used in the proposed framework to store access control policies safely on the blockchain. The framework also penalizes users for attempting unauthorized access to the IoT resources. The smart contract was developed using Remix and deployed on the Ropsten Ethereum testnet. We analyze the performance of the smart contract-based access policies based on the gas consumption of blockchain transactions. Further, we analyze the system’s security, usability, scalability, and interoperability performance.
... Because of these applications, millions of individuals can access timely health information that may help them make informed decisions about their health and well-being. With the recent emergence of Blockchain technology for eHealth, a secure, decentralized, and patient-driven record management system is possible [102]. Since the use case for storing IoT data collected in remote patient management (RPM) situations necessitates a rapid consensus process, careful keys management, and improved privacy safeguards, Blockchain technology cannot handle such storage. ...
There has been a rise in the demand for blockchain-based smart contract development platforms and language implementations. On the other hand, smart contracts and blockchain applications are generated using non-standard software life cycles, which means that, for example, distributed applications are rarely updated, or bugs are fully addressed by releasing a newer version, leading to security flaws and challenges for users to adopt the technology. Smart contracts have gained significant attention due to their potential to automate and secure various transactions in diverse domains. However, the increasing adoption of smart contracts has also raised concerns about security vulnerabilities and potential risks. In this paper, an overview of smart contracts was discussed in detail. It further distinguished and compared smart contracts security with conventional security regarding security, privacy, communication channel, etc. Different platforms for smart contracts, such as Bitcoin, Ethereum, Counterparty, Stellar, Monax, and Lisk, are also discussed in this paper. Some proposed techniques are used in different areas for handling security threats in smart contracts. In addition, a taxonomy of the smart contracts security application was proposed, which attempts to solve some of the flaws and inadequacies in smart contracts. The study also provides a comprehensive smart contracts security scenario with different techniques. Lastly, the possible attacks posed by threats and vulnerabilities of the smart contracts are provided. The security threats and vulnerabilities addressed in this study are unique to smart contracts.
... References [30,31] are on EHR systems and [32,33] are on IoT-based healthcare systems. Some studies [36][37][38][39][40] use a patient-centric agent to preserve privacy in IoT-based healthcare systems. Besides, a group of other studies [41,42] focuses on reducing the computational overhead through network clustering in IoTbased healthcare systems. ...
... However, the proposed scheme leads to high computational overhead for users. Uddin et al. [38,39] propose a decentralized BC-based healthcare system. The patient-centric agent is introduced to preserve the privacy and security of patients while outsourcing patients' tasks to the edge and cloud nodes. ...
In Internet-of-Things (IoT)-based healthcare systems, real-time healthcare data are gathered from patients’ sensors with limited resources and transferred to end-users through gateways and healthcare service providers. Privacy of patients is a main challenge of these systems. Although privacy has already been considered in IoT-based healthcare systems, best centralized approaches yet suffer from collusion attack. Therefore, some researchers have come up with blockchain-based solutions to protect patients’ privacy in IoT-based healthcare systems. However, those methods assume that parts of the entities along the end-to-end communication path from patients’ sensors to the end-users are trusted or even assuming no privacy threats from internal attackers. Therefore, there is a lack of a blockchain-based approach in IoT-based healthcare systems to provide privacy for patients, assuming that all system entities are untrusted. To overcome these challenges, in this paper, we leverage a three-layered hierarchical blockchain, the zero-knowledge proof (ZKP), and the ring signature method to achieve data and location privacy of patients against both internal and external attackers. In addition, the proposed method provides anonymous authentication, authorization, and scalability, which are essential features in healthcare systems. Intuitive and formal security analyses demonstrate the resilience of our scheme against various attacks such as denial of service (DoS), modification, mining, storage, and replay attacks. The proposed method is compared to a recent blockchain-based method and also a centralized privacy-preserving scheme. Compared to the similar blockchain-based method, the computational overhead and delay of the authentication and data transfer phase are about 35% and 37% higher, respectively. Instead, the proposed method reduces memory usage of gateways by about 55% and diminishes the computational overhead and delay of information access phase by about 30% and 33% compared to the previous blockchain-based method. Therefore, the proposed method does not increase overhead and end-to-end delay considerably compared to the previous blockchain-based scheme, while some other performance metrics and security features are improved. Moreover, compared to a previous centralized method, the proposed approach shows more than 25% decrease in communication overhead and 22% improvement in memory usage of gateways, in average. Although the use of the blockchain imposes more computational overhead on service providers and may increase the latency compared to the centralized approach (depending on the type of the blockchain technology that is used), these weaknesses are negligible at the expense of increased security.
... Edge devices through edge network and smart contract push data into data storage. Xu et al. [18] and Uddin [19] et al. describe that edge devices can help reduce the load on the main or cloud server. ...
For dispute resolution in daily life, tamper-proof data storage and retrieval of log data are important with the incorporation of trustworthy access control for the related users and devices, while giving access to confidential data to the relevant users and maintaining data persistency are two major challenges in information security. This research uses blockchain data structure to maintain data persistency. On the other hand, we propose protocols for the authentication of users (persons and devices) to edge server and edge server to main server. Our proposed framework also provides access to forensic users according to their relevant roles and privilege attributes. For the access control of forensic users, a hybrid attribute and role-based access control (ARBAC) module added with the framework. The proposed framework is composed of an immutable blockchain-based data storage with endpoint authentication and attribute role-based user access control system. We simulate authentication protocols of the framework in AVISPA. Our result analysis shows that several security issues can efficiently be dealt with by the proposed framework.
... These research outcomes have been summarized in this section and presented in Table 3. The framework for BC-based storage of data generated through IoT-based healthcare equipment was proposed by [51] and guaranteed patient safety. The proposed framework contains a virtual patient agent (PA), specifying the capabilities of BC. ...
The Internet of Things (IoT) and blockchain (BC) are reliable technologies widely employed in various contexts. IoT devices have a lot of potential for data sensing and recording without human intervention, but they also have processing and security issues. Due to their limited computing power, IoT devices cannot use specialized cryptographic security mechanisms. There are various challenges when using traditional cryptographic techniques to transport and store medical records securely. The general public's health depends on having an electronic health record (EHR) system that is current. In the era of e-health and m-health, problems with integrating data from various EHRs, preserving data interoperability, and ensuring that all data access is in the patient's hands are all obstacles to creating a dependable EHR system. If health records get into the wrong hands, they could endanger the lives of patients and their right to privacy. BC technology has become a potent tool for ensuring recorded data's immutability, validity, and confidentiality while enabling decentralized storage. This study focuses on EHR and other types of e-healthcare, evaluating the advantages of complementary technologies and the underlying functional principles. The major BC consensus mechanisms for BC-based EHR systems are analyzed in this study. It also examines several IoT-EHR frameworks' current infrastructures. A breakdown of BC integration's benefits with the IoT-EHR framework is also offered. A BC-based IoT-EHR architecture has been developed to enable the automated sensing of patient records and to store and retrieve these records in a secure and reliable environment. Finally, we conduct a security study to demonstrate the security of our suggested EHR framework.
... Moreover, in the near future, the deep learning model will also play a vital role to combat the pandemic. A plan for future work is to explore federated learning on blockchain technology [88] to build a distributed trust-less COVID-19 detection system. Despite the fact that we collected a huge number of chest X-ray images to train our model, it still has to be tested with a large number of patient images from various nations to ensure its reliability. ...
Citation: Ahamed, M.K.U.; Islam, M.M.; Uddin, M.A.; Akhter, A.; Acharjee, U.K.; Paul, B.K.; Moni, M.A. Abstract: COVID-19 is a severe respiratory contagious disease that has now spread all over the world. COVID-19 has terribly impacted public health, daily lives and the global economy. Although some developed countries have advanced well in detecting and bearing this coronavirus, most developing countries are having difficulty in detecting COVID-19 cases for the mass population. In many countries, there is a scarcity of COVID-19 testing kits and other resources due to the increasing rate of COVID-19 infections. Therefore, this deficit of testing resources and the increasing figure of daily cases encouraged us to improve a deep learning model to aid clinicians, radiologists and provide timely assistance to patients. In this article, an efficient deep learning-based model to detect COVID-19 cases that utilizes a chest X-ray images dataset has been proposed and investigated. The proposed model is developed based on ResNet50V2 architecture. The base architecture of ResNet50V2 is concatenated with six extra layers to make the model more robust and efficient. Finally, a Grad-CAM-based discriminative localization is used to readily interpret the detection of radiological images. Two datasets were gathered from different sources that are publicly available with class labels: normal, confirmed COVID-19, bacterial pneumonia and viral pneumonia cases. Our proposed model obtained a comprehensive accuracy of 99.51% for four-class cases (COVID-19/normal/bacterial pneumonia/viral pneumonia) on Dataset-2, 96.52% for the cases with three classes (normal/COVID-19/bacterial pneumonia) and 99.13% for the cases with two classes (COVID-19/normal) on Dataset-1. The accuracy level of the proposed model might motivate radiologists to rapidly detect and diagnose COVID-19 cases.
... As a result, categorizing similar information utilizing current approaches could result in miscommunications as well as open-ended problems. This would improve the robustness and efficiency of IoV based healthcare systems [7,26]. ...
... The two fundamental kinds of memory space are: whenever users create an instantiation of a structural, object, or property. The complexities arise here for providing latency-less and prompt access to the healthcare data [26,30]. Healthcare professionals may decrease hospitalizations, cut down on inaccuracies, and more accurately pinpoint groups at concern by evaluating health information. ...
... Besides, it also provides distributed computing solutions for handling heterogeneous medical data. This would improve the robustness and efficiency of IoV based healthcare systems [7,26]. ...
Internet of Vehicles (IoV) assisted healthcare systems are designed for providing reliable and dynamic medical assistance for the connected users/ patients. The healthcare systems inherit the intelligent computing models in Internet of Vehicles (IoV) for processing user requests and allocating medical data. In this manuscript, the problem is due to stagnancy in request processing and latency in response dissemination, which is addressed using a responsive data-sharing framework (RDSF). This framework is designed for addressing the afore-mentioned issues in healthcare data searching and allocation. The proposed framework performs searching, organizing, and data allocation without stagnancy in request processing. In this processing, K-means clustering is deployed to differentiate and classify the allocation and searching instances and interrupt in different time intervals. The proposed framework identifies the interrupting instances for improving the response allocation ratio. The linearization of the classification and allocation of the clustering process reduces the complexity in handling healthcare data. The proposed framework’s performance shows that it is capable of improving data handling rate by reducing complexity, latency, and request failures. The proposed EDSF increases data response by 12.8%, reduces response latency and interrupt complexity by 7.65% and 10.55% respectively.
... However, the increasing usage of IoT devices brings some additional challenges that are associated with privacy, immutability, reliability, and performance [3]. Traditional IoT service architectures involve the transmission of data captured by IoT devices to cloud entities that third parties manage. ...
... Traditional IoT service architectures involve the transmission of data captured by IoT devices to cloud entities that third parties manage. Third-party management makes maintaining data privacy and data security difficult [3]. ...
... In [5], they proposed an end-to-end PCA-controlled eHealth architecture where the PCA manages storage on the BC, determines the security and privacy level for a patient, and selects a single miner to generate PoW using a secretary optimization algorithm. Uddin et al. [3], [10] suggested a decentralized PCA to replicate it on the three levels, including the Smartphone, Fog, and Cloud level, to coordinate a portion of blockchain on the Fog and other portions of the BC on the Cloud network. The decentralized PCA was employed to withstand major cyber attacks. ...
Blockchain (BC) is a burgeoning technology that has emerged as a promising solution to peer-to-peer communication security and privacy challenges. As a revolutionary technology, blockchain has drawn the attention of academics and researchers. Cryptocurrencies have already effectively utilized BC technology. Many researchers have sought to implement this technique in different sectors, including the Internet of Things. To store and manage IoT data, we present in this paper a lightweight BC-based architecture with a modified raft algorithm-based consensus protocol. We designed a Device Agent that executes a novel registration procedure to connect IoT devices to the blockchain. We implemented the framework on Docker using the Go programming language. We have simulated the framework on a Linux environment hosted in the cloud. We have conducted a detailed performance analysis using a variety of measures. The results demonstrate that our suggested solution is suitable for facilitating the management of IoT data with increased security and privacy. In terms of throughput and block generation time, the results indicate that our solution might be 40% to 45% faster than the existing blockchain.
... The proposed architecture is wellsuited to event-driven IoT devices, and it makes use of the edge and cloudlet computing paradigms, as well as Hierarchical Identity Based Encryption (HIBE) for privacy protection, in which the ciphertext comprises only three group components, and decryption needs only two bilinear map calculations. Uddin et al. [162] suggested a decentralized eHealth architecture based on BC technology. To guarantee patient privacy while outsourcing duties, a patient agent program uses a lightweight BC consensus mechanism and a BC leveraged task-offloading algorithm [162]. ...
... Uddin et al. [162] suggested a decentralized eHealth architecture based on BC technology. To guarantee patient privacy while outsourcing duties, a patient agent program uses a lightweight BC consensus mechanism and a BC leveraged task-offloading algorithm [162]. ...
... For BC, privacy-preserving strategies based on encryption approaches are evolving, allowing users to become anonymous and have the ability to manage their personal data (e.g., what, whom, and when personal data can be shared in each transaction). Authors proposed several mechanisms to enhance privacy ( [70,88,115,116,162,169,217]); to enable and enhance identification ( [61,129,136,172,174,209,218]), to ensure data privacy ( [97,146,188]), and to enhance location privacy ( [83,165,192,198]). The majority of the selected studies under this category reported that BC can enhance the level of privacy, in general, followed by identification, and the least purpose mentioned was to achieve data privacy. ...
The fog computing concept was proposed to help cloud computing for the data processing of Internet of Things (IoT) applications. However, fog computing faces several challenges such as security, privacy, and storage. One way to address these challenges is to integrate blockchain with fog computing. There are several applications of blockchain-fog computing integration that have been proposed, recently, due to their lucrative benefits such as enhancing security and privacy. There is a need to systematically review and synthesize the literature on this topic of blockchain-fog computing integration. The purposes of integrating blockchain and fog computing were determined using a systematic literature review approach and tailored search criteria established from the research questions. In this research, 181 relevant papers were found and reviewed. The results showed that the authors proposed the combination of blockchain and fog computing for several purposes such as security, privacy, access control, and trust management. A lack of standards and laws may make it difficult for blockchain and fog computing to be integrated in the future, particularly in light of newly developed technologies like quantum computing and artificial intelligence. The findings of this paper serve as a resource for researchers and practitioners of blockchain-fog computing integration for future research and designs.
