基于熵的社交网络虚假个人资料识别

Geetika Sarna, M. Bhatia
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引用次数: 0

摘要

网络欺凌是一种通过在网上发送骚扰/尴尬/辱骂信息对受害者实施的重罪行为。通常情况下,罪犯创建虚假档案是为了隐藏自己的身份,从事不道德的活动。假设一个假身份是非常有害的,因为罪犯的真实照片是不可见的,而且很难诱骗他们。有时,一些值得信赖的朋友也会利用假身份来伤害受害者。罪犯可以泄露受害者的个人信息,如财务细节、个人历史、家庭等,同时,他可以用虚假的个人资料骚扰、威胁或勒索受害者,并将这些信息渗透到社交网络上。因此,有必要解决这个问题。在本文中,作者使用熵和交叉熵的概念来识别虚假配置文件,因为熵在不确定程度上起作用。并将本文提出的方法与现有的分类器进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entropy Based Identification of Fake Profiles in Social Network
Cyberbullying is a felonious act carried out against the victim by sending harassing/ embarrassing/ abusing information online. Normally offenders create fake profiles in order to hide their identity for unscrupulous activities. Assuming a fake identity is very harmful as the real picture of the offender is not visible, and also it can become difficult to entrap them. Sometimes, some trustworthy friends can also take advantage of the fake identity in order to harm the victim. Culprits can reveal victim's personal information like financial details, personal history, family, etc., and along with it, he can harass, threaten or blackmail the victim using fake profiles and permeates that information on the social network. So, it is necessary to resolve this issue. In this article, the authors used the concept of entropy and cross entropy to identify fake profiles as entropy works on the degree of uncertainty. Also, this article shows the comparison of proposed method with the existing classifiers.
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