Sanitizing Social Networks Against Information Inference Attack |
Author(s): |
| L.Syed Magdoom Rafeek , B.S.AbdurRahman University, Chennai; C.Imthyaz Sheriff, B.S.AbdurRahman University, Chennai |
Keywords: |
| Online social networks, business success |
Abstract |
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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. This project explores how to launch inference attacks using released social networking data to predict private information. Then devise three possible sanitization techniques that could be used in various situations. This project explore the effectiveness of these techniques and attempt to use methods of collective inference to discover sensitive attributes of the data set. This project shows that there can be increase in the effectiveness of both local and relational classification algorithms by using the sanitization methods described. |
Other Details |
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Paper ID: IJSRDV3I30343 Published in: Volume : 3, Issue : 3 Publication Date: 01/06/2015 Page(s): 688-690 |
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