Crowd-BT: A Bilateral Trustworthy Ensured Scheme for Blockchain-Assisted Mobile Crowdsensing

Blockchain-based distributed mobile crowdsensing (MCS) has been widely adopted in areas, such as the Industrial Internet of Things (IIoT) to transform traditional data collection methods. However, existing works lack a theory-driven quantitative utility analysis and precise reward and punishment measures that effectively deter malicious behavior. This deficiency hinders the ability to constrain rational participants’ behavior, thereby compromising the trustworthiness of MCS implementations. To address the issue above, this article proposes Crowd-BT: a bilateral trustworthy ensured scheme for blockchain assisted MCS. Specifically, Crowd-BT first devises reward and punishment measures based on participants’ short-term utility analysis for an unrestricted context in the ideal case. Then, for the more practical situation, Crowd-BT designs blocklist punishment measures for participants, ensuring self-containment based on long-term utility analysis. Finally, leveraging the practical blocklist punishment measures and the devised anonymity behavior record certificates (ABRCs) using the message-hidden signature, Crowd-BT details the implementation steps for MCS under the blockchain. Theoretical analysis shows that Crowd-BT achieves both utility and security goals. Extensive experiments illustrate that Crowd-BT effectively constrains participant behavior. Compared to the existing works, it significantly enhances the trustworthiness of MCS.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-11-27
DOI
https://doi.org/10.1109/jiot.2024.3505948
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
0.00

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article

Crowd-BT: A Bilateral Trustworthy Ensured Scheme for Blockchain-Assisted Mobile Crowdsensing

Zoe L. Jiang, Bin Luo, Y. Yao, Yong Yu et al.
IEEE Internet of Things Journal
Mobile Crowdsensing and Crowdsourcing
article

Crowd-BT: A Bilateral Trustworthy Ensured Scheme for Blockchain-Assisted Mobile Crowdsensing

Zoe L. Jiang, Bin Luo, Y. Yao, Yong Yu, Jianyong Fan
article en

Abstract

Blockchain-based distributed mobile crowdsensing (MCS) has been widely adopted in areas, such as the Industrial Internet of Things (IIoT) to transform traditional data collection methods. However, existing works lack a theory-driven quantitative utility analysis and precise reward and punishment measures that effectively deter malicious behavior. This deficiency hinders the ability to constrain rational participants’ behavior, thereby compromising the trustworthiness of MCS implementations. To address the issue above, this article proposes Crowd-BT: a bilateral trustworthy ensured scheme for blockchain assisted MCS. Specifically, Crowd-BT first devises reward and punishment measures based on participants’ short-term utility analysis for an unrestricted context in the ideal case. Then, for the more practical situation, Crowd-BT designs blocklist punishment measures for participants, ensuring self-containment based on long-term utility analysis. Finally, leveraging the practical blocklist punishment measures and the devised anonymity behavior record certificates (ABRCs) using the message-hidden signature, Crowd-BT details the implementation steps for MCS under the blockchain. Theoretical analysis shows that Crowd-BT achieves both utility and security goals. Extensive experiments illustrate that Crowd-BT effectively constrains participant behavior. Compared to the existing works, it significantly enhances the trustworthiness of MCS.

IEEE Internet of Things JournalVol. 12(10)
Northwestern Polytechnical University (CN), Harbin Institute of Technology (CN), Shaanxi Normal University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, Key Research and Development Projects of Shaanxi Province
Openalex Percentile: Top 78%
Mobile Crowdsensing and Crowdsourcing
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