Literature Database Entry

yu2024correlation-aware

Dongxiao Yu, Kaiyi Zhang, Youming Tao, Wenlu Xu, Yifei Zou and Xiuzhen Cheng, "Correlation-Aware and Personalized Privacy-Preserving Data Collection," Proceedings of IEEE International Conference on Computing, Networking and Communications (ICNC 2024), Kailua, HI, February 2024.

Abstract

Data collection from users is essential for various IoT services. However, privacy concerns may prevent users from sharing their raw data truthfully. The problem becomes more complex when the data and relationships are correlated and the privacy preferences are personalized. In particular, users’ data are influenced by social interactions, which implies that others' data can affect users' privacy. Moreover, users care not only about their own privacy leakage, but also about their social contacts' privacy leakage, due to the social ties in reality. Furthermore, different users have different levels of privacy sensitivity for their own data, which poses a challenge for balancing user privacy and data utility. In this paper, we investigate the correlation-aware and personalized private data collection problem. We formulate the private data collection process as a Stackelberg game, where the platform sets its reward policy and users select their noise levels for privacy preservation. To tackle the challenges above, we adopt the Gaussian correlation model to represent the data correlation among users and integrate the relationship correlation and personalization when deriving the optimal strategies for both users and the platform. Notably, we employ mutual information differential privacy for a rigorous quantification of the correlated privacy loss. Through rigorous theoretical analysis, we first establish the connection between users' Nash equilibrium and the payment mechanism, and then optimize the platform's accuracy under a budget constraint by designing the reward policy. We also demonstrate the effective- ness of our proposed framework through extensive numerical experiments.

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Dongxiao Yu
Kaiyi Zhang
Youming Tao
Wenlu Xu
Yifei Zou
Xiuzhen Cheng

BibTeX reference

@inproceedings{yu2024correlation-aware,
    author = {Yu, Dongxiao and Zhang, Kaiyi and Tao, Youming and Xu, Wenlu and Zou, Yifei and Cheng, Xiuzhen},
    title = {{Correlation-Aware and Personalized Privacy-Preserving Data Collection}},
    publisher = {IEEE},
    address = {Kailua, HI},
    booktitle = {IEEE International Conference on Computing, Networking and Communications (ICNC 2024)},
    month = {2},
    year = {2024},
   }
   
   

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