Blockchain technology and IoT-edge framework for sharing healthcare services

El_Rahman, Sahar A.; Alluhaidan, Ala Saleh

doi:10.1007/s00500-021-06041-4

Cited by 31 publications

(17 citation statements)

References 73 publications

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“…In this context, we compared the proposed QoS-ledger with the state-of-the-art methods, such as "Blockchain technology and IoT-edge framework for sharing healthcare services" and "Blockchain Technology in Healthcare Industry". S. A. El-Rahman and A. S. Alluhaidan proposed an IoT-edge framework for the purpose of sharing medical information without changing utilizing data processing and blockchain techniques [42]. This proposed system works on the predefined mechanism of blockchain, which is less cost-effective for processing medical records and transmission over the defined network, whereas the QoS-ledger provides a customized blockchain consortium network environment, which creates more reliability between elderly devices connectivity with the secure transmission, shown in Chaincode 1 and 2.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

QoS-Ledger: Smart Contracts and Metaheuristic for Secure Quality-of-Service and Cost-Efficient Scheduling of Medical-Data Processing

et al. 2021

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Quality-of-service (QoS) is the term used to evaluate the overall performance of a service. In healthcare applications, efficient computation of QoS is one of the mandatory requirements during the processing of medical records through smart measurement methods. Medical services often involve the transmission of demanding information. Thus, there are stringent requirements for secure, intelligent, public-network quality-of-service. This paper contributes to three different aspects. First, we propose a novel metaheuristic approach for medical cost-efficient task schedules, where an intelligent scheduler manages the tasks, such as the rate of service schedule, and lists items utilized by users during the data processing and computation through the fog node. Second, the QoS efficient-computation algorithm, which effectively monitors performance according to the indicator (parameter) with the analysis mechanism of quality-of-experience (QoE), has been developed. Third, a framework of blockchain-distributed technology-enabled QoS (QoS-ledger) computation in healthcare applications is proposed in a permissionless public peer-to-peer (P2P) network, which stores medical processed information in a distributed ledger. We have designed and deployed smart contracts for secure medical-data transmission and processing in serverless peering networks and handled overall node-protected interactions and preserved logs in a blockchain distributed ledger. The simulation result shows that QoS is computed on the blockchain public network with transmission power = average of −10 to −17 dBm, jitter = 34 ms, delay = average of 87 to 95 ms, throughput = 185 bytes, duty cycle = 8%, route of delivery and response back variable. Thus, the proposed QoS-ledger is a potential candidate for the computation of quality-of-service that is not limited to e-healthcare distributed applications.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

QoS-Ledger: Smart Contracts and Metaheuristic for Secure Quality-of-Service and Cost-Efficient Scheduling of Medical-Data Processing

et al. 2021

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“…At first, the distribution of attention to all the input data is determined, which is followed by the determination of the weighted average of the input data. The attention for all the given inputs is determined using Equation (10).…”

Section: User Authentication Model With Developed Ad-lstm-anmentioning

confidence: 99%

“…9 The centralized information storage system leads to a number of problems, including Denial of Service (DoS), hacking of patients' health and personal information, and untrustworthy third-party intervention to store healthcare data. 10 However, conventional strategies for the confidentiality and safety of patient information storage systems are ineffective in healthcare settings because of the intensive memory and computation processes, and the interference of noises in the gathered information reduces the data's usefulness in smart healthcare. 11 Studies suggested using blockchain in medical facilities to avert these security and confidentiality problems.…”

Section: Introductionmentioning

confidence: 99%

HECC‐ABE: A novel blockchain‐based IoT healthcare data storage using hybrid cryptography schemes with key optimization by hybrid meta‐heuristic algorithm

Dubey,

Ramanjaneyulu,

Saraswat

et al. 2023

Trans Emerging Tel Tech

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The most contemporary development in information technology is the Internet of Things (IoT), which integrates the digital world with the real world. It makes it possible for things and people to communicate via the Internet. Blockchain is one of the popular topics of interest right now, and it can be used in most IoT applications. The blockchain's salient characteristics, like decentralization, data integrity, confidentiality, protection, and openness, are the main reasons for implementing it in healthcare services. Hence, this paper introduces an effective approach for storing IoT‐based healthcare data storage in the blockchain. The procedures in this suggested paradigm are as follows: user authentication, user trust verification, and optimal key storage in the blockchain. Wearable sensors are inserted in or adhered to a patient's body and used by IoT networks to gather healthcare data. These details are supplied into the verification structure constructed by adaptive dilated long short term memory with attention network (AD‐LSTM‐AN). Once the user's authentication is confirmed, then the user's trust level is computed. The same AD‐LSTM‐AN‐based verification structure is used to verify the historical data that has been stored and retrieved by the user, together with their previous transactions, in this phase. The healthcare data are then sent to the hybrid elliptic curve cryptography with attribute‐based encryption (HECC‐ABE) cryptography schemes for data encryption once the authentication of the person who attempts to store the data is confirmed. An adaptive final position‐based golden eagle‐Harris hawks optimization (AFP‐GEHHO) algorithm is used for optimizing the keys of the encrypted data. The blockchain platform stores the encrypted data of the authorized user with a high level of trust. The same process is done in reverse order whenever a user needs to recover information that is saved in the blockchain to retrieve the initially stored healthcare data. The effectiveness of secure data storage in blockchain is tested through experimental simulations. Throughout the analysis, the designed model achieves 96% in terms of accuracy. Thus, the developed model shows more secure and effective, has less error and reduces the time and memory requirements compared to existing approaches.

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“…ElRahman and Alluhaidan [ 10 ] introduced a blockchain-based approach to secure healthcare IoT systems. The proposed framework designs a trust model to prevent data leakage.…”

Section: Related Workmentioning

confidence: 99%

A Novel Edge-Based Trust Management System for the Smart City Environment Using Eigenvector Analysis

Nagarajan

Simpson²,

Venkatachalam

et al. 2022

Journal of Healthcare Engineering

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The proposed Edge-based Trust Management System (E-TMS) uses an Eigenvector-based approach for eliminating the security threats present in the Internet of Things (IoT) enabled smart city environment. In most existing trust management systems, the trust aggregation process completely depends on the direct trust ratings obtained from both legitimate and malicious neighboring IoT devices. E-TMS possesses an edge-assisted two-level trust computation approach for ensuring the malicious free trust evaluation of IoT devices. The E-TMS aims at removing the false contribution on aggregated trust data. It utilizes the properties of the Eigenvector for identifying compromised IoT devices. The Eigenvector Analysis also helps to avoid false detection. The analysis involves a comparison of all the contributed trust data about every single connected device. A spectral matrix will be generated corresponding to the contributions and the received trust will be scaled based on the obtained spectral values. The absolute sum of obtained values will contain only true contributions. The accurate identification of false data will remove the effect of malicious contributions from the final trust value of a connected IoT device. Since the final trust value calculated by the edge node contains only the trustworthy data, the prediction about the malicious nodes will be accurate. Eventually, the performance of E-TMS has been validated. Throughput and network resilience are higher than the existing system.

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Blockchain technology and IoT-edge framework for sharing healthcare services

Cited by 31 publications

References 73 publications

QoS-Ledger: Smart Contracts and Metaheuristic for Secure Quality-of-Service and Cost-Efficient Scheduling of Medical-Data Processing

QoS-Ledger: Smart Contracts and Metaheuristic for Secure Quality-of-Service and Cost-Efficient Scheduling of Medical-Data Processing

HECC‐ABE: A novel blockchain‐based IoT healthcare data storage using hybrid cryptography schemes with key optimization by hybrid meta‐heuristic algorithm

A Novel Edge-Based Trust Management System for the Smart City Environment Using Eigenvector Analysis

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