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Tweet Analysis for Malicious Content Using Hybrid System

Author(s):

Aditya Jadhav , Savitribai Phule University of Pune, Modern Education Society College of Engineering ; Aditya Jadhav, Savitribai Phule University of Pune, Modern Education Society College of Engineering ; Shital Salve, Savitribai Phule University of Pune, Modern Education Society College of Engineering

Keywords:

Phishing, Information Security, Machine Learning, Classifier

Abstract

Spamming is common in various types of automated communication sources including email, instant messaging, and social networks. To reach more users numerous spammers now use various content-sharing platforms including online social networks— to publicize spam such as twitter. Twitter has become one of the furthermost used social networks. And, as happens with every common media, it is susceptible to misuse. In this environment, spam in Twitter has developed in the last years, becoming a significant problem for the users. In the last years, numerous methods have appeared that are able to determine whether a user is a spammer or not. However, these debarring systems cannot filter every spam message (snippet) and a spammer may make another account and restart sending spam. As there are methods to filter spam text contents, Spammers now using the idea of spam images? So a proficient spam image filter is must. These spam messages contains phish links, so here we need phish link filter. By keeping eye on this problems of twitter, we proposed here a “Twitter Spam Filter” an application to filter spam images, unsolicited tweets and phish links from tweets.

Other Details

Paper ID: IJSRDV4I30026
Published in: Volume : 4, Issue : 3
Publication Date: 01/06/2016
Page(s): 33-37

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