Privacy-Preserved Network Data Publishing

  • Lei Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6637)


Nowadays, more and more people join multiple social networks on the Web, such as Facebook, Linkedin, and Livespace, to share their own information and at the same time to monitor or participate in different activities. Meanwhile, the information stored in the social networks are under high risk of attack by various malicious users, in other words, peoples privacy could be easily breached via some domain knowledge. Thus, as a service provider, such as Facebook and Linkedin, it is essential to protect users privacy and at the same time provide useful data. Simply removing all identifiable personal information (such as names and social security number) before releasing the data is insufficient. It is easy for an attacker to identify the target by performing different structural queries.


Social Network Service Provider Knowledge Discovery Personal Information Domain Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Lei Chen
    • 1
  1. 1.Hong Kong University of Science and TechnologyHong Kong

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