A privacy-preserving model to control social interaction behaviors in social network sites

Sanaz Kavianpour*, Ali Tamimi, Bharanidharan Shanmugam

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
200 Downloads (Pure)


Social Network Sites (SNSs) served as an invaluable platform to transfer information across a large number of users. SNSs also disseminate users data to third-parties to provide more interesting services for users as well as gaining profits. Users grant access to third-parties to use their services, although they do not necessarily protect users’ data privacy. Controlling social network data diffusion among users and third-parties is difficult due to the vast amount of data. Hence, undesirable users’ data diffusion to unauthorized parties in SNSs may endanger users’ privacy. This paper highlights the privacy breaches on SNSs and emphasizes the most significant privacy issues to users. The goals of this paper are to i) propose a privacy-preserving model for social interactions among users and third-parties; ii) enhance users’ privacy by providing access to the data for appropriate third-parties. These advocate to not compromising the advantages of SNSs information sharing functionalities.
Original languageEnglish
Article number102402
Number of pages8
JournalJournal of Information Security and Applications
Early online date7 Nov 2019
Publication statusPublished - 1 Dec 2019


  • Annonymization
  • Classification
  • Privacy
  • Social interaction behaviors
  • Social network sites


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