Providing Group Anonymity in Social Networks



In today’s world, there are almost no borders between people. Using Internet technologies, especially social networks, people can communicate and share different information regardless of where they live or work. However, giving out any sensitive information can pose significant security threats for the owner of the information. As more privacy challenges arise, people become concerned about their security. Many social networking websites provide various types of privacy policies, but this proves to be insufficient. All existing security methods aim at gaining individual anonymity. Nevertheless, information about user groups, which could be determined inside social networks, is not protected. Still, this information might occur to be security-intensive information is present in this data set. In this chapter, the task we have set is providing group anonymity in social networks. By group anonymity we understand the property of a group of people to be indistinguishable within a particular dataset. We also propose a technique to solve the task using wavelet transforms.


Social Network Wavelet Transform Initial Dataset Goal Representation Privacy Preference 
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.


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Copyright information

© Springer-Verlag London 2012

Authors and Affiliations

  1. 1.Kyiv Polytechnic InstituteNational Technical University of UkraineKyivUkraine

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