From tag to protect: A tag-driven policy recommender system for image sharing

Anna Cinzia Squicciarini, Andrea Novelli, Dan Lin, Cornelia Caragea, Haoti Zhong

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

2 Scopus citations

Abstract

Sharing images on social network sites has become a part of daily routine for more and more online users. However, in face of the considerable amount of images shared online, it is not a trivial task for a person to manually configure proper privacy settings for each of the images that he/she uploaded. The lack of proper privacy protection during image sharing could raise many potential privacy breaches of people's private lives that they are not aware of. In this work, we propose a privacy setting recommender system to help people effortlessly set up the privacy settings for their online images. The key idea is developed based on our finding that there are certain correlations between a number of generic patterns of image privacy settings and image tags, regardless of the image owners' individual privacy bias and levels of awareness. We propose a multi-pronged mechanism that carefully analyzes tags' semantics and co-presence to derive a set of suitable privacy settings for a newly uploaded image. Our system is also capable of dealing with cold-start problem when there are very few image tags available. We have conducted extensive experimental studies and the results demonstrate the effectiveness of our approach in terms of the policy recommendation accuracy.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 15th Annual Conference on Privacy, Security and Trust, PST 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages337-346
Number of pages10
ISBN (Electronic)9781538624876
DOIs
StatePublished - Sep 28 2018
Event15th Annual Conference on Privacy, Security and Trust, PST 2017 - Calgary, Canada
Duration: Aug 27 2017Aug 29 2017

Publication series

NameProceedings - 2017 15th Annual Conference on Privacy, Security and Trust, PST 2017

Other

Other15th Annual Conference on Privacy, Security and Trust, PST 2017
CountryCanada
CityCalgary
Period8/27/178/29/17

All Science Journal Classification (ASJC) codes

  • Information Systems and Management
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality

Fingerprint Dive into the research topics of 'From tag to protect: A tag-driven policy recommender system for image sharing'. Together they form a unique fingerprint.

Cite this