Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Khan, Abdullah Ayub; Shaikh, Zaffar Ahmed; Laghari, Asif Ali; Bourouis, Sami; Wagan, Asif Ali; Ali, Ghulam Ali Alias Atif

doi:10.3390/atmos12111525

Cited by 19 publications

(15 citation statements)

References 46 publications

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“…Privacy and preservation are the main agendas that require maintenance and traceability. A distributed storage structure needs to be arranged so that it cannot create additional slots and focuses on the management of meta record storage [38,39]. Thus, maintaining the integrity and confidentiality of records and consistency of distributed educational applications during sharing is a complex task for an immutable storage structure with scalability and availability.…”

Section: Credential Privacy and Preservation Challengesmentioning

confidence: 99%

“…Various educational problems are associated with the current centralized accreditation system, including an analysis system for detecting errors in digital educational transactions, especially keeping secure credential information in central storage and relying on the cloud solution for preservation and security [36,38,40]. In addition, there are inappropriate techniques and inappropriate mechanisms used to register the device, collect universities' records, and accredit it.…”

Section: Governance Body and Compliance Related Limitationsmentioning

confidence: 99%

“…The major challenging aspect of accreditation is to provide candidates' certificatesensitive credentials transparency in a distributed environment [36,37]. The hyperledger sawtooth enables the provision of pre-defined information integrity and confidentiality policies [38]. In the proposed model, we have designed and created a customized protection mechanism using hash-encryption (SHA-256), which manages overall educational node transaction verification and validation, and implemented a consensus policy (PoET: range of parameter tuned) that allows for efficient performance in terms of security, privacy, and protection.…”

Section: Accreditation Transparency For Hedmentioning

confidence: 99%

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Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture

et al. 2022

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This paper proposes a novel and secure blockchain hyperledger sawtooth-enabled consortium analytical model for smart educational accreditation credential evaluation. Indeed, candidate academic credentials are generated, verified, and validated by the universities and transmitted to the Higher Education Department (HED). The objective is to enable the procedure of credential verification and analyze tamper-proof forged records before validation. For this reason, we designed and created an accreditation analytical model to investigate individual collected credentials from universities and examine candidates’ records of credibility using machine learning techniques and maintain all these aspects of analysis and addresses in the distributed storage with a secure hash-encryption (SHA-256) blockchain consortium network, which runs on a peer-to-peer (P2P) structure. In this proposed analytical model, we deployed a blockchain distributed mechanism to investigate the examiner and analyst processes of accreditation credential protection and storage criteria, which are referred to as chaincodes or smart contracts. These chaincodes automate the distributed credential schedule, generation, verification, validation, and monitoring of the overall model nodes’ transactions. The chaincodes include candidate registration with the associated university (candidateReg()), certificate-related accreditation credentials update (CIssuanceTrans()), and every node’s transactions preservation in the immutable storage (ULedgerAV()) for further investigations. This model simulates the educational benchmark dataset. The result shows the merit of our model. Through extensive simulations, the blockchain-enabled analytical model provides robust performance in terms of credential management and accreditation credibility problems.

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Section: Credential Privacy and Preservation Challengesmentioning

confidence: 99%

Section: Governance Body and Compliance Related Limitationsmentioning

confidence: 99%

Section: Accreditation Transparency For Hedmentioning

confidence: 99%

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Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture

et al. 2022

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“…The blockchain decentralized mechanism manages all the patients' logs transparently and makes patient data available on a technology rife for security distributed applications. Substantially, blockchain does not only provide transparency; it manages medical ledgers privately, concealing the patient's identity with complex hash-based encryption and secure codes that tackle protection-related challenges and make sensitive medical records safe in the immutable storage [36,37]. Moreover, the distributed nature of blockchain healthcare allows stakeholders to exchange the same information more quickly and efficiently.…”

Section: A Layered Hierarchy Of Medical Dikw and Blockchainmentioning

confidence: 99%

BIoMT Modular Infrastructure: The Recent Challenges, Issues, and Limitations in Blockchain Hyperledger-Enabled E-Healthcare Application

Shaikh

Khan

Teng

et al. 2022

Wireless Communications and Mobile Computing

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This paper presents a layered hierarchy that depicts the progressive relationship between data, information, knowledge, and wisdom. To begin with, data is gathered and organized into information. Information is gathered, filtered, refined, and put through an investigation process to create knowledge. Wisdom is attained after knowledge discovery through the process of filtration and aggregation through experience. The layered hierarchy in the domain of e-healthcare necessitates higher scheduling costs for data collection, processing wisdom, and management, which is also an insecure and untrustworthy process for progressive medical service. The medical industry faces a difficult problem in providing collected data integrity, information reliability, and knowledge trustworthiness for the service of progressive medical relationships in the face of an increasing number of day-to-day records. The blockchain consortium hyperledger (fabric) has been used in this paper to act as a bridge that bridges the gap between electronic data, information, knowledge, and wisdom (DIKW) movement and processes by enabling the process of the layered hierarchy of schedule information and management and providing security and transparency. For e-healthcare information management and privacy, the DIKW-ledger, such as patients’ consultancy information, availing medical services, personal records, appointments, treatment details, and other health-related transactions, a consortium hyperledger fabric-enabled efficient architecture is proposed. This proposed architecture creates two networks: a public network for medical stakeholders to exchange and agree on specific medical activities before being preserved on distributed storage (read-only after record registration) and a private network for complete DIKW process scheduling and management. We designed and created smart contracts for this purpose, as well as use-case diagrams to describe the overall execution process. The proposed architectural solution provides more efficient information integrity, provenance, and storage procedures to immutably preserve the medical ledger in a permissioned hash-encrypted structure.

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“…The Federal Healthcare Authority needs to collaborate with the other private healthcare service delivery organizations and information security providers for secure serverless distributed network transmission. Whereas QoS and metaheuristic-enabled cost-effective scheduling of medical-data processing via e-healthcare DApps that evaluate the healthcare environment to calculate differences and formulate new authoritative policies and objectives [49,50].…”

Section: Compliance and Regulation Issues In E-healthcare Systemsmentioning

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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Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Cited by 19 publications

References 46 publications

Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture

Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture

BIoMT Modular Infrastructure: The Recent Challenges, Issues, and Limitations in Blockchain Hyperledger-Enabled E-Healthcare Application

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

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