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An Application of Random Walk on Fake Account Detection Problem: A Hybrid Approach

机译:随机游走在虚假账户检测问题中的应用:一种混合方法

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In the world we are living now, it’s very difficult to find a people who access to Internet regularly but own no social network account. Social networks play a significant and day by day, more important role. People use Facebook or Twitter for communicating, news reading, information sharing, and advertising. However, these social networks lead to some issues. One of which is the need for a defense mechanism against fake accounts. To separate fake accounts from authentic ones is obviously a non trivial task. In this paper, we propose an empirical ranking scheme, comprising of both graph-based and feature-based approaches to aid the detection of fake Facebook profiles. Utilizing Support Vector Machine (SVM) [4] and Sybil- Walk [8], the model achieved high accuracy over the set of ten thousands Vietnamese Facebook accounts.
机译:在我们现在生活的世界上,很难找到一个定期访问互联网但没有社交网络帐户的人。社交网络每天都扮演着重要的角色。人们使用Facebook或Twitter进行交流,新闻阅读,信息共享和广告。但是,这些社交网络会导致一些问题。其中之一是需要一种针对虚假帐户的防御机制。将伪造账户与真实账户分开显然不是一件容易的事。在本文中,我们提出了一种经验排名方案,该方案包括基于图的方法和基于特征的方法,以帮助检测假Facebook个人资料。利用支持向量机(SVM)[4]和Sybil-Walk [8],该模型在上万个越南Facebook帐户集上实现了高精度。

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