Privacy preserving event sequence data visualization using a sankey diagram-like representation

Jia Kai Chou, Yang Wang, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Given the growing rates and richness of data being collected nowadays, it is non-trivial for data owners to determine a single best publishing granularity that presents the most value of the data while preserving its privacy. There have been extensive studies on privacy preserving algorithms in the data mining community, but relatively few have been done to provide a supervised control over the anonymization process. We present the design and evaluation of a visual interface that assists users to employ commonly used data anonymization techniques for making privacy preserving visualizations of the data. We focus on event sequence data due to its vulnerability to privacy concerns. Our visual interface is designed for data owners to examine potential privacy issues, obfuscate information as suggested by the algorithm, and fine-tune the results per their requests. Case studies using multiple datasets under different scenarios demonstrate the effectiveness of our design. These studies show that using visualization as an interface can help identify potential privacy issues, reveal underlying anonymization processes, and allow users to balance between data utility and privacy.

Original languageEnglish (US)
Title of host publicationSA 2016 - SIGGRAPH ASIA 2016 Symposium on Visualization
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450345477
DOIs
StatePublished - Nov 28 2016
Event2016 SIGGRAPH ASIA Symposium on Visualization, SA 2016 - Macau, China
Duration: Dec 5 2016Dec 8 2016

Other

Other2016 SIGGRAPH ASIA Symposium on Visualization, SA 2016
CountryChina
CityMacau
Period12/5/1612/8/16

Fingerprint

Data visualization
Visualization
Data mining

Keywords

  • Event sequence data analysis
  • Privacy preserving visualization

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software
  • Computer Graphics and Computer-Aided Design

Cite this

Chou, J. K., Wang, Y., & Ma, K-L. (2016). Privacy preserving event sequence data visualization using a sankey diagram-like representation. In SA 2016 - SIGGRAPH ASIA 2016 Symposium on Visualization [a1] Association for Computing Machinery, Inc. https://doi.org/10.1145/3002151.3002153

Privacy preserving event sequence data visualization using a sankey diagram-like representation. / Chou, Jia Kai; Wang, Yang; Ma, Kwan-Liu.

SA 2016 - SIGGRAPH ASIA 2016 Symposium on Visualization. Association for Computing Machinery, Inc, 2016. a1.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chou, JK, Wang, Y & Ma, K-L 2016, Privacy preserving event sequence data visualization using a sankey diagram-like representation. in SA 2016 - SIGGRAPH ASIA 2016 Symposium on Visualization., a1, Association for Computing Machinery, Inc, 2016 SIGGRAPH ASIA Symposium on Visualization, SA 2016, Macau, China, 12/5/16. https://doi.org/10.1145/3002151.3002153
Chou JK, Wang Y, Ma K-L. Privacy preserving event sequence data visualization using a sankey diagram-like representation. In SA 2016 - SIGGRAPH ASIA 2016 Symposium on Visualization. Association for Computing Machinery, Inc. 2016. a1 https://doi.org/10.1145/3002151.3002153
Chou, Jia Kai ; Wang, Yang ; Ma, Kwan-Liu. / Privacy preserving event sequence data visualization using a sankey diagram-like representation. SA 2016 - SIGGRAPH ASIA 2016 Symposium on Visualization. Association for Computing Machinery, Inc, 2016.
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