|
| | | | |
| | | |
| Stat |
Members: 3644
Articles: 2'499'343
Articles rated: 2609
16 April 2024 |
|
| | | | |
|
Article overview
| |
|
|
OPTT: Optimal Piecewise Transformation Technique for Analyzing Numerical Data under Local Differential Privacy | | Fei Ma
; Renbo Zhu
; Ping Wang
; | | Date: |
9 Dec 2021 | | Abstract: | Privacy preserving data analysis (PPDA) has received increasing attention due
to a great variety of applications. Local differential privacy (LDP), as an
emerging standard that is suitable for PPDA, has been widely deployed into
various real-world scenarios to analyze massive data while protecting against
many forms of privacy breach. In this study, we are mainly concerned with
piecewise transformation technique (PTT) for analyzing numerical data under
local differential privacy. We provide a principled framework for PTT in the
context of LDP, based on which PTT is studied systematically. As a result, we
show that (1) many members in PTTs are asymptotically optimal when used to
obtain an unbiased estimator for mean of numerical data, and (2) for a given
privacy budget, there is PTT that reaches the theoretical low bound with
respect to variance. Next, we prove by studying two classes of PTTs in detail
that (1) there do not exist optimal PTTs compared to the well-used technique,
i.e., Duchi’s scheme, in terms of the consistency noisy variance, (2) on the
other hand, one has the ability to find a great number of PTTs that are
consistently more optimal than the latter with regard to the worst-case noisy
variance, which is never reported so far. When we are restricted to consider
only the high privacy level, enough PTTs turn out to be optimal than the
well-known Laplace mechanism. Lastly, we prove that for a family of PTTs, the
correspondingly theoretical low bound of noisy variance follows
$O(epsilon^{-2})$ when considering the high privacy level. | | Source: | arXiv, 2112.04745 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser claudebot
|
| |
|
|
|
|
News, job offers and information for researchers and scientists:
| |
REGISTER