reviewACM Computing SurveysJan 6, 2022Closed access

A Survey on Differential Privacy for Unstructured Data Content

YZYing ZhaoJCJinjun Chen

Swinburne University of Technology

Indexed incrossref

Abstract

Huge amounts of unstructured data including image, video, audio, and text are ubiquitously generated and shared, and it is a challenge to protect sensitive personal information in them, such as human faces, voiceprints, and authorships. Differential privacy is the standard privacy protection technology that provides rigorous privacy guarantees for various data. This survey summarizes and analyzes differential privacy solutions to protect unstructured data content before it is shared with untrusted parties. These differential privacy methods obfuscate unstructured data after they are represented with vectors and then reconstruct them with obfuscated vectors. We summarize specific privacy models and mechanisms…

Citation impact

286
total citations
FWCI
37.73
Percentile
100%
References
107
Citations per year

Authors

2

Topics & keywords

Topics
Keywords
  • Differential privacy
  • Computer science
  • Internet privacy
  • Privacy protection
  • Computer security
  • Privacy software
  • Unstructured data
  • Differential (mechanical device)
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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