A New Approach for Detection of Cloned Accounts in Online Social Networks using Fuzzy Logic

چکیده مقاله

Social networking websites are becoming common. Well-known websites, such as Twitter and Facebook, have millions of users worldwide. With the development of these networks, there are security and privacy threats for social media users, such as privacy violation, viral marketing, structured attacks, middleware attacks and account cloning. This study investigates the detection of cloned accounts in social networks. For this purpose, the standard KONECT dataset is used, which is defined as a social network graph, including records for cloned accounts. The proposed system includes a system consisting of the average fuzzy clustering and the fuzzy inference system developed by Mamdani. In this study, to evaluate efficiency of the proposed method, all steps in the standard KONECT dataset are implemented in Facebook, and finally, this research work is compared with the three previous studies investigating the same dataset.

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