Building a Secure Knowledge Marketplace over Crowdsensed Data Streams

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

5 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)2601-2616
Journal / PublicationIEEE Transactions on Dependable and Secure Computing
Volume18
Issue number6
Online published10 Dec 2019
Publication statusPublished - Nov 2021

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