Preventing Private Information Inference Attacks on Online Social Networks
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 8
Abstract
On-line social networks like Facebook are increasingly utilized by many people. These networks allow users to publish their own details and enable them to contact their friends. Some of the information revealed inside these networks is private. But it is possible that corporations could use learning algorithms on released data to predict undisclosed private information. In this work, ways to launch inference attacks are explored using released social networking data to predict unrevealed private information about personalities. Then three possible sanitization techniques that could be used in various situations are devised.The effectiveness of these techniques are evaluated by implementing them on a dataset.
Authors and Affiliations
Ramya R
Keywords
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