Local differential Privacy for Belief Functions

Authors

Qiyu Li, Renmin University Of China
Chunlai Zhou, Renmin University of China
Biao Qin, Renmin University of China
Zhiqiang Xu, Mohamed bin Zayed University of Artificial IntelligenceFollow

Document Type

Article

Publication Title

arXiv

Abstract

In this paper, we propose two new definitions of local differential privacy for belief functions. One is based on Shafer's semantics of randomly coded messages and the other from the perspective of imprecise probabilities. We show that such basic properties as composition and post-processing also hold for our new definitions. Moreover, we provide a hypothesis testing framework for these definitions and study the effect of "don't know" in the trade-off between privacy and utility in discrete distribution estimation. Copyright © 2022, The Authors. All rights reserved.

DOI

10.48550/arXiv.2202.08576

Publication Date

2-17-2022

Keywords

Cryptography

Comments

Preprint: arXiv

Recommended Citation

Q. Li, C. Zhou, B. Qin, and Z. Xu, "Local differential privacy for belief functions," 2022, arXiv:2202.08576