Crowd-BT: A Bilateral Trustworthy Ensured Scheme for Blockchain-Assisted Mobile Crowdsensing
Bin Luo, Yong Yu, Zoe L. Jiang, Yuchao Yao, Jianyong Fan · IEEE Internet of Things Journal · 2024
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.