基于机器学习技术的社交网络欺诈账户检测

E. Anupriya, N. Kumaresan, V. Suresh, S. Dhanasekaran, K. Ramprathap, P. Chinnasamy
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引用次数: 0

摘要

如今,一个人的影响力往往取决于他或她在社交媒体上的粉丝数量。为了实现这一目标,虚假账户的盛行是最紧迫的问题之一,有可能破坏广泛的现实世界和经济活动。机器人粉丝对社交媒体来说是危险的,因为它们可能会改变人们对受欢迎程度和影响力的看法,这可能会对每个行业产生巨大的影响。因此,必须开发新的方法来检测和分类虚假账户。该研究为原始轮廓的识别提供了一种新的方法。该方法利用从海量数据中自动收集的信息,对虚假账户的典型模式进行表征。
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Fraud Account Detection on Social Network using Machine Learning Techniques
Nowadays, a person's impact is frequently determined by the number of followers he or she has on social media. To this aim, the prevalence of false accounts is one of the most pressing issues, with the potential to disrupt a wide range of real-world and economic activity. Bot followers are dangerous to social media as these could alter perceptions of popularity and influence, which can have a ample amount of impact on every sector. As a result, new approaches must be developed to enable the detection and classification of bogus accounts. This study gives novel method for distinguishing original profiles. The method uses information gathered automatically from huge data to characterize typical patterns of fake account.
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