A Secure Framework for Protection of Social Networks from Information Stealing Attacks

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Provided by: The International Journal of Innovative Research in Computer and Communication Engineering
Format: PDF
Social networks are online applications that allow their users to connect by means of various link types. Since these sites gather extensive personal information, there is a promising chance for leakage of personal information and inference attacks. To prevent the social networks from such attacks, a secure framework is proposed here. As first step, the social network is modeled as a connected graph where nodes and edges represent users of network and relationships among them respectively. Then three kinds of learning methods are applied for modeling the inference attacks.
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