Balancing Privacy-Utility of Differential Privacy Mechanism: A Collaborative Perspective

Author:

Liu Hai123ORCID,Peng Changgen123ORCID,Tian Youliang23,Long Shigong23,Wu Zhenqiang4

Affiliation:

1. Guizhou Big Data Academy, Guizhou University, Guiyang 550025, China

2. College of Computer Science and Technology, Guizhou University, Guiyang 550025, China

3. State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China

4. School of Computer Science, Shaanxi Normal University, Xi’an 710119, China

Abstract

Differential privacy mechanism can maintain privacy-utility monotonicity. Thus, differential privacy mechanism does not obtain privacy-utility balance for numerical data. To this end, we provide privacy-utility balance of differential privacy mechanism with the collaborative perspective in this paper. First, we constructed the collaborative model achieving privacy-utility balance of differential privacy mechanism. Second, we presented the collaborative algorithm of differential privacy mechanism under our collaborative model. Third, our theoretical analysis showed that the collaborative algorithm of differential privacy mechanism could keep privacy-utility balance. Finally, our experimental results demonstrated that the collaborative differential privacy mechanism can maintain privacy-utility balance. Thus, we provide a new collaborative model to solve the privacy-utility balance problem of differential privacy mechanism. Our collaborative algorithm is easy to apply to query processing of numerical data.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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