Trust-preserving mechanism for blockchain assisted mobile crowdsensing

Zhang, L., Feng, G., Qin, S., Li, X., Sun, Y. and Cao, B. (2023) Trust-preserving mechanism for blockchain assisted mobile crowdsensing. IEEE Transactions on Computers, 72(11), pp. 3113-3126. (doi: 10.1109/TC.2023.3287043)

Abstract

Blockchain is envisioned as one of the promising technologies to address trust concern brought by mobile crowdsensing (MCS), due to its auditability, immutability and decentralization. Nevertheless, blockchain cannot fundamentally guarantee that the valuable sensed data outside the chain can enter the chain, although data integrity and consistency can be ensured once it is confirmed inside the chain. In addition, simply applying blockchain in MCS while ignoring possible abnormal saboteurs hidden in numerous devices may mislead the normal operation of blockchain, resulting in untrustworthy interactions. Consequently, it is highly desirable to build a trust-preserving mechanism (TPM) to fully enjoy the benefits of using blockchain in MCS. To this end, we first resort to a probabilistic trust assessment inferred from the interaction outcomes in blockchain, to incentivize participants to maintain the trustworthiness of interactions. By inferring trust to aid decision-making, trust decision is further made, including leader election and transaction data generation, to filter untrusted nodes from participating in blockchain process. Finally, extensive simulations are conducted to validate the effectiveness and efficiency of TPM, and improve the performance in terms of contribution rate, consensus accuracy and system stability.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Sun, Dr Yao and Feng, Professor Gang
• Authors: Zhang, L., Feng, G., Qin, S., Li, X., Sun, Y., and Cao, B.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: IEEE Transactions on Computers
• Publisher: IEEE
• ISSN: 0018-9340
• ISSN (Online): 1557-9956
• Published Online: 19 June 2023
• Copyright Holders: Copyright © 2023 IEEE
• First Published: First published in IEEE Transactions on Computers 72(11):3113 - 3126
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher