An Effective Method for Detection of Untruthful Interpretations in Public Networks
Author(s):
KRISHNAIAH BOYANA, Dr.G.Venkateswara Rao, Mr.K.Bhaskara Rao, Mr.P.Ratna Prakash
Keywords:
Social Networks, TPR (True +Ve rate) and FPR (False +Ve rate), Uniform Resource locator
Abstract
Social Networks (SNs) have become indispensable parts of our daily lives in recent years, and their popularity is growing at an incredible rate. However, in addition to the revolution that Social Networks have wrought in community interaction, they have also posed a slew of challenges, one of which is the difficulty of categorizing bogus factions as humanoid, bot, or cyborg. We need a system that can detect the most recent social engineering attacks and help the study of live Twitter data. The system application that will be built can also be made available for use, and the data will be stored and created on the server. Such a system's design must protect user privacy, be user-friendly, and detect account misconduct. Furthermore, the detecting system should assign a score to the false user so that they can determine their level of genuineness, as well as allow a legitimate user to erase spam from their profile.
Article Details
Unique Paper ID: 154565

Publication Volume & Issue: Volume 8, Issue 11

Page(s): 528 - 532
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