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    When Blockchain Meets Edge Intelligence: Trusted and Security Solutions for Consumers

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    Date
    2021-09-01
    Author
    Gupta, Rajesh
    Reebadiya, Dakshita
    Tanwar, Sudeep
    Kumar, Neeraj
    Guizani, Mohsen
    Metadata
    Show full item record
    Abstract
    Nowadays, mission-critical applications need delay-free responses, which can be achieved by computation at the edge devices known as edge computing. But edge computing needs cloud computing services to perform massive intelligent tasks like AI-based prediction and analysis, which still possesses high latency in making intelligent decisions. This can be resolved by bringing intelligence at the edge device or edge server, which introduces complex problems either at the proximity of edge devices, that is, consumer electronic devices (CED), or at the CED by bringing intelligence at the edge. The process of bringing intelligence to the edge is called edge intelligence (EI). The computation at edge servers is susceptible to various security and privacy issues and possesses high latency due to data propagation from the device to the dedicated edge server. To overcome the aforementioned issues, this study presents a blockchain-based edge intelligence system to ensure the CEDs' data security, privacy, latency, and efficiency. The proposed system uses public and private blockchains to fulfil the gaps mentioned above of the traditional systems. The public blockchain ensures CEDs' data communication privacy security, whereas private block-chain ensures secure communication among the EI servers. Then, we present the use case scenario of blockchain and edge intelligence (EI) in the COVID-19 pandemic and evaluate its performance over computation cost by comparing the intelligence at CED with the intelligence at the edge server and centralized cloud server (CCS).
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85118258854&origin=inward
    DOI/handle
    http://dx.doi.org/10.1109/MNET.001.2000735
    http://hdl.handle.net/10576/35591
    Collections
    • Computer Science & Engineering [‎2428‎ items ]

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