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
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews