On Privacy Preserving Partial Image Sharing

Jianping He, Bin Liu, Xuan Bao, Hongxia Jin, George Kesidis

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

2 Scopus citations


Sharing photos through Online Social Networks becomes an increasingly popular fashion. However, users' privacy may be at stake when sensitive photos are shared improperly. This paper presents a dynamic privacy protection technique (named PuPPIeS) for image data where the data owner stipulates small private regions for sensitive objects (faces, SSN numbers, etc.) of a photo/image and sets different sharing policies for these partial regions with respect to different individuals. PuPPIeS is based on optimized reversible matrix perturbation of compressed image data. Hence it can naturally support frequently used image transformations. Our experiments show that our solution is effective for privacy protection and incurs only a small overhead for partial image sharing.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems, ICDCS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages2
ISBN (Electronic)9781467372145
StatePublished - Jul 22 2015
Event35th IEEE International Conference on Distributed Computing Systems, ICDCS 2015 - Columbus, United States
Duration: Jun 29 2015Jul 2 2015

Publication series

NameProceedings - International Conference on Distributed Computing Systems


Other35th IEEE International Conference on Distributed Computing Systems, ICDCS 2015
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


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