Prevention of Fake Accounts in Online Social Media by Face Detection

Abstract

The Growth of Social Networks are increasingly popular in the world nowadays, as well as people’s social lives are increasingly linked to these sites. The social media platforms are used every day and have become a key component of our lives. Fake profiles are used primarily by invaders to conduct harmful activities, including theft of identity and violation of the privacy of the online social network (OSN). Therefore, understanding a true or false account is one of the main problems for OSN. Social networks are easily corrupted by automated fake identities that impose excessive control. A whole black-market services industry has emerged that provides counterfeit account-based services for sale. Some techniques of machine learning have been used to detect fake accounts, but the re-search work involved is very limited to consider counterfeit identities generated by individuals. however, researchers have begun to investigate successful strate-gies for detecting suspicious behavior and fraudulent accounts based on account-ing properties, In order to accomplish the task of detecting, identifying and pre-venting the creation fake accounts we establish Convolution neural networks .In this paper, we are implementing a face recognition and age classification  mechanism by using CNN to prevent the creation of fake accounts in Online Social Networks.