Abstract
Now a day’s many people are rapidly increases the use of social networks like facebook. By using these networks so many number of users are connected with their friends and relatives. Some of the user related data should be private in the networks. To launch presumption attacks using released social networking data to forecast personal data. Three possible refining techniques that could be used in different situations. Discover the effectiveness of these techniques and challenge to use methods of collective presumption to discover sensitive attributes of the data set. So then decrease the effectiveness of both local and relational classification algorithms by using the sanitization methods can describe.