An incentive mechanism for privacy preserved data trading with verifiable data disturbance
Publication Type
Journal Article
Publication Date
7-2025
Abstract
To motivate data owners’ (DOs’) trading willingness, the existing incentive mechanisms allow DOs to independently disturb data following data consumer's (DC’s) availability requirement. However, they cannot motivate DOs’ honest disturbance, which is attributed to DOs’ independent disturbance without any supervision. Thus, we implement an incentive mechanism for privacy preserved data trading with verifiable data disturbance where an honest-but-curious disturbance generator (DG) is additionally introduced to supervise DOs’ local disturbance and assist disturbance verification between DOs and DC. Specifically, DG generates the disturbance strategies and secretly distributes to DOs following private information retrieval, guaranteeing DOs's local disturbance's privacy and verifiability with our proposed three-level verification algorithm. Subsequently, we model the trading as a game and disturbance verification results determine the compensation and punishment for trading bilateral utilities following Nash Equilibrium where DOs honestly disturb data. Theoretical analysis shows that DOs are motivated to honestly disturb data and their raw data privacy is preserved. Extensive experiments using the real-world dataset demonstrate that the deviating DOs in our scheme can be verified with a probability of more than 90% and the statistical result accuracy can be improved by more than 80% compared with the existing works.
Keywords
Incentive mechanisms, data trading, availability requirement, privacy requirements, game theory
Discipline
Information Security
Research Areas
Information Systems and Management
Publication
IEEE Transactions on Dependable and Secure Computing
Volume
22
Issue
4
First Page
3960
Last Page
3976
ISSN
1545-5971
Identifier
10.1109/TDSC.2025.3542773
Publisher
Institute of Electrical and Electronics Engineers
Citation
ZHANG, Man; LI, Xinghua; LUO, Bin; REN, Yanbing; MIAO, Yinbin; LIU, Ximeng; and DENG, Robert H..
An incentive mechanism for privacy preserved data trading with verifiable data disturbance. (2025). IEEE Transactions on Dependable and Secure Computing. 22, (4), 3960-3976.
Available at: https://ink.library.smu.edu.sg/sis_research/10444
Additional URL
https://doi.org/10.1109/TDSC.2025.3542773