Don’t peek at my chart: Privacy-preserving visualization for mobile devices

Publication Type

Journal Article

Publication Date

6-2023

Abstract

Data visualizations have been widely used on mobile devices like smartphones for various tasks (e.g., visualizing personal health and financial data), making it convenient for people to view such data anytime and anywhere. However, others nearby can also easily peek at the visualizations, resulting in personal data disclosure. In this paper, we propose a perception-driven approach to transform mobile data visualizations into privacy-preserving ones. Specifically, based on human visual perception, we develop a masking scheme to adjust the spatial frequency and luminance contrast of colored visualizations. The resulting visualization retains its original information in close proximity but reduces visibility when viewed from a certain distance or farther away. We conducted two user studies to inform the design of our approach (N=16) and systematically evaluate its performance (N=18), respectively. The results demonstrate the effectiveness of our approach in terms of privacy preservation for mobile data visualizations.

Discipline

Databases and Information Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Computer Graphics Forum

Volume

42

Issue

3

First Page

137

Last Page

148

ISSN

0167-7055

Identifier

10.1111/cgf.14818

Publisher

Wiley

Additional URL

https://doi.org/10.1111/cgf.14818

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