Two-Phase Preference Disclosure in Attributed Social Networks

  • Younes Abid
  • Abdessamad Imine
  • Amedeo Napoli
  • Chedy Raïssi
  • Michaël RusinowitchEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10438)


In order to demonstrate privacy threats in social networks we show how to infer user preferences by random walks in a multiple graph representing simultaneously attributes and relationships links. For the approach to scale in a first phase we reduce the space of attribute values by partition in balanced homogeneous clusters. Following the Deepwalk approach, the random walks are considered as sentences. Hence unsupervised learning techniques from natural languages processing can be employed in second phase to deduce semantic similarities of some attributes. We conduct initial experiments on real datasets to evaluate our approach.


Online social network (OSN) Attribute disclosure attacks Privacy 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Younes Abid
    • 1
  • Abdessamad Imine
    • 1
  • Amedeo Napoli
    • 1
  • Chedy Raïssi
    • 1
  • Michaël Rusinowitch
    • 1
    Email author
  1. 1.Lorraine University, CNRS, InriaNancyFrance

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