Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41378

A Peer-Based Approach on Analyzing Hacked Twitter Accounts

File SizeFormat 
paper0229.pdf2.25 MBAdobe PDFView/Open

Item Summary

Title: A Peer-Based Approach on Analyzing Hacked Twitter Accounts
Authors: Murauer, Benjamin
Zangerle, Eva
Specht, Günther
Keywords: hacked account detection
social media analysis
Twitter
Issue Date: 04 Jan 2017
Abstract: Social media has become an important part of the lives of their hundreds of millions of users. Hackers make use of the large target audience by sending malicious content, often by hijacking existing accounts. This phenomenon has caused widespread research on how to detect hacked accounts, where different approaches exist. This work sets out to analyze the possibilities of including the reactions of hacked Twitter accounts’ peers into a detection system. Based on a dataset of six million tweets crawled from Twitter over the course of two years, we select a subset of tweets in which users react to alleged hacks of other accounts. We then gather and analyze the responses to those messages to reconstruct the conversations made. A quantitative analysis of these conversations shows that 30% of the users that are allegedly being hacked reply to the accusations, suggesting that these users acknowledge that their account was hacked.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41378
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.224
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Data Analytics and Data Mining for Social Media Minitrack



Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.