Re-Fake: Fake Account Classification in OSN Using RNN

Re-Fake: Fake Account Classification in OSN Using RNN

Classification, Fake Accounts, Recurrent Neural Network, Deep Learning

Online Social Network (OSN) is an application for enabling public communication and sharing information. However, the fake account in the OSN can spread false information froman unknown source. It is a challenging task to detect malicious accounts in a large OSN system. The existence of fake accounts or unknown accounts on OSN can be a severe issue in data privacy-preserving. Various communities have proposed many techniques to deal with fake accounts in OSN, including rule-based black-white techniquesuntil learning approaches. Therefore, in this study,we propose a classification model using the RNN to detect fake accounts accurately and effectively. We conduct this study in several steps, including gathering datasets, pre-processing, extraction, and training our models using RNN. Based on the experiment result, our proposed model can produce a higher accuracy than the conventional learning model

Romana Herlinda

https://ijicom.respati.ac.id/index.php/ijicom/article/view/48/34

August 2022

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