Preventing Private Information Inference Attacks on Social Networks

@article{Heatherly2013PreventingPI,
  title={Preventing Private Information Inference Attacks on Social Networks},
  author={Raymond Heatherly and Murat Kantarcioglu and Bhavani M. Thuraisingham},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2013},
  volume={25},
  pages={1849-1862}
}
Online social networks, such as Facebook, are increasingly utilized by many people. These networks allow users to publish details about themselves and to connect to their friends. Some of the information revealed inside these networks is meant to be private. Yet it is possible to use learning algorithms on released data to predict private information. In this paper, we explore how to launch inference attacks using released social networking data to predict private information. We then devise… CONTINUE READING
Highly Cited
This paper has 122 citations. REVIEW CITATIONS

6 Figures & Tables

Topics

Statistics

0204020112012201320142015201620172018
Citations per Year

123 Citations

Semantic Scholar estimates that this publication has 123 citations based on the available data.

See our FAQ for additional information.