Building a Secure Knowledge Marketplace over Crowdsensed Data Streams
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 2601-2616 |
Journal / Publication | IEEE Transactions on Dependable and Secure Computing |
Volume | 18 |
Issue number | 6 |
Online published | 10 Dec 2019 |
Publication status | Published - Nov 2021 |
Link(s)
Abstract
It is increasingly popular to leverage the wisdom of crowd for knowledge discovery and monetization. Among others, crowdsensing with truth discovery has emerged as a promising way for leveraging the crowd wisdom, which can mine reliable knowledge from unreliable sensory data contributed from diverse sources. Building a knowledge marketplace based on crowdsensing with truth discovery for knowledge discovery and monetization, however, is challenging. Firstly, the sensory data should be protected as they may carry sensitive information. Secondly, real crowdsensing applications usually yield sensory data in a streaming fashion, posing the demand that truth discovery should be conducted over data streams to continuously mine reliable knowledge. Thirdly, knowledge monetization should be well treated, fully addressing the practical needs of parties. In this paper, we take the first research attempt and propose a new framework for building a secure knowledge marketplace over crowdsensed data streams. Our framework leverages lightweight cryptographic techniques like secret sharing to enable privacy-preserving streaming truth discovery. For monetization of the learned truth, i.e., knowledge, we resort to the emerging blockchain technology and deliver a tailored and full-fledged design, which promises monetization fairness, knowledge confidentiality, and streamlined processing. Extensive experiments have demonstrated the practically affordable performance of our design.
Research Area(s)
- Encrypted blockchain applications, truth discovery, crowdsensing systems, privacy
Citation Format(s)
Building a Secure Knowledge Marketplace over Crowdsensed Data Streams. / Cai, Chengjun; Zheng, Yifeng; Zhou, Anxin et al.
In: IEEE Transactions on Dependable and Secure Computing, Vol. 18, No. 6, 11.2021, p. 2601-2616.
In: IEEE Transactions on Dependable and Secure Computing, Vol. 18, No. 6, 11.2021, p. 2601-2616.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review