使用机器学习技术在社交网络中伪造个人资料

M. A. Jyothi, T. Sridevi, KV Rajani, Ugranada Channabasava, Srikanth Bethu
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摘要

每天都有越来越多的人在社交媒体平台上注册账户,但出于恶意,他们隐瞒了自己的身份。遗憾的是,到目前为止,我们已经做了一个小调查,以确定个人主要在社交媒体上设计的假身份。相比之下,由于假账户是由自动化或个人电脑生成的,并利用机器学习技术的模型挖掘出来的,因此以案例的形式存在着巨大的样本。在自动化的情况下,机器学习模型依赖于被设计对象的属性,如同伴与追随者的比例。这些属性是从同伴数量和追随者数量等特征中得出的,这些特征可以在社交媒体的个人资料中直接获得。本文讨论的调查呼吁对虚假账户进行类似的属性,因此会有一些希望对媒体平台上个人生成的虚假个人资料进行检测。
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Rapport of Counterfeit Profiles in Social Networking using Machine Learning Techniques
Day-By-Day the number is been increasing of individuals who clench accounts on the platform named social media but they conceal their identity for the motives of malevolent. Regrettably, we have done a small investigation to date to determine fake identifications that are been designed by the individuals mainly on social media. In the contradistinction, huge samples are subsisted in the form of cases as the fake accounts are been generated by automation or personal computers and these are dug out by utilizing the models of machine learning techniques. In the case of automation, models of machine learning are depending on the attributes of the engineered employing as the proportion of companion to followers. These attributes are brought out from the features like the count of the companion and the count of the follower that is straightly obtainable in the profiles of the social media. The investigation debated in this paper appeals to the similar attributes for the fake accounts so there will be some desire of proceeding the fake profiles detection which are been generated by individuals on the medial platform.
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