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    Secure Crowdsensed Data Trading Based on Blockchain

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    Type
    Article
    Authors
    An, Baoyi
    Xiao, Mingjun
    Liu, An
    Xu, Yun
    Zhang, Xiangliang cc
    Li, Qing
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Machine Intelligence & kNowledge Engineering Lab
    Date
    2021
    Permanent link to this record
    http://hdl.handle.net/10754/670754
    
    Metadata
    Show full item record
    Abstract
    Crowdsensed Data Trading (CDT) is a novel data trading paradigm, where each data consumer can publicize its data demand as some crowdsensing tasks, and some mobile users (i.e., data sellers) can compete for these tasks, collect the corresponding data, and sell the results to the consumers. Existing CDT systems generally depend on a data trading broker, which will inevitably cause consumers concerns on the trustworthiness of the systems and truthfulness of the data. To address this problem, we propose a Blockchain-based Crowdsensed Data Trading (BCDT) system, mainly containing a smart contract, called BCDToken. First, we replace the broker with blockchain to guarantee the trustworthiness of data trading. Meanwhile, BCDToken adopts Blockchain-based Reverse Auction (BRA) to assign tasks to data sellers. BRA holds truthfulness and individual rationality, which can ensure the sellers to report costs honestly and prevent sellers to manipulate the auction. Moreover, we implement a Secure Truth Discovery and reliability Rating (STDR) mechanism in BCDToken based on homomorphic cryptography, which can incentivize sellers to upload the truthful data and consumers to rate truthfully the reliabilities of sellers without revealing any privacy of data. Additionally, we also deploy BCDToken to the test network to demonstrate its practicability.
    Citation
    An, B., Xiao, M., Liu, A., Xu, Y., Zhang, X., & Li, Q. (2021). Secure Crowdsensed Data Trading Based on Blockchain. IEEE Transactions on Mobile Computing, 1–1. doi:10.1109/tmc.2021.3107187
    Publisher
    IEEE
    Journal
    IEEE Transactions on Mobile Computing
    DOI
    10.1109/TMC.2021.3107187
    Additional Links
    https://ieeexplore.ieee.org/document/9521727/
    https://ieeexplore.ieee.org/document/9521727/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9521727
    ae974a485f413a2113503eed53cd6c53
    10.1109/TMC.2021.3107187
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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