Multi-round efficient and secure truth discovery in mobile crowdsensing systems
Publication Type
Journal Article
Publication Date
1-2024
Abstract
Privacy-preserving truth discovery, as a data aggregation algorithm that can extract reliable results from disparate and conflicting data in a privacy-preserving manner, has received a lot of attention in ensuring the reliability and privacy of data in mobile crowdsensing systems. However, most of the existing work requires that workers must stay online all the time during the full process of truth discovery. Although a few recent schemes have been proposed to tolerate worker dropout, they are tailored for a single-round setting. Repeating these schemes several times to adapt to the truth discovery will introduce significant computational and communication overheads, especially for the workers. To solve the above challenges, in this paper, we propose a multi-round efficient and secure truth discovery scheme in mobile crowdsensing systems that can balance the 3-way trade-off between privacy protection, dropout tolerance, and protocol efficiency. Specifically, we devise a novel mask generation capable of reusing secrets to eliminate the costly overhead of workers needing to recompute new secrets each round. Besides, we design a lightweight dropout tolerance mechanism to guarantee that even if workers drop out halfway, the server can still acquire meaningful truth. Rigorous security analysis and extensive experimental results demonstrate the privacy and efficiency of our scheme, respectively.
Keywords
Crowdsensing, Data privacy, Dropout tolerance, Mask generation, Mobile crowdsensing, Multi-round, Privacy, Privacy-preserving, Protocols, Sensors, Servers, Task analysis, Truth discovery
Discipline
Information Security
Publication
IEEE Internet of Things Journal
ISSN
2327-4662
Identifier
10.1109/JIOT.2024.3359757
Publisher
Institute of Electrical and Electronics Engineers
Citation
HU, Chenfei; LI, Zihan; XU, Yuhua; ZHANG, Chuan; LIU, Ximeng; HE, Daojing; and ZHU, Liehuang.
Multi-round efficient and secure truth discovery in mobile crowdsensing systems. (2024). IEEE Internet of Things Journal.
Available at: https://ink.library.smu.edu.sg/sis_research/8666
Copyright Owner and License
Authors
Additional URL
https://doi.org/10.1109/JIOT.2024.3359757