Skip to main content
USENIX
  • Conferences
  • Students
Sign in
  • LEET '12 Home
  • Registration Information
  • Organizers
  • Workshop Program
  • Hotel & Travel Information
  • Students
  • Questions?
  • For Participants
  • Call for Papers
  • Past Proceedings

sponsors

General Sponsor

twitter

Tweets by @usenix

usenix conference policies

  • Event Code of Conduct
  • Conference Network Policy
  • Statement on Environmental Responsibility Policy

You are here

Home » Adapting Social Spam Infrastructure for Political Censorship
Tweet

connect with us

http://twitter.com/usenix

Adapting Social Spam Infrastructure for Political Censorship

Authors: 

Kurt Thomas and Chris Grier, University of California, Berkeley; Vern Paxson, University of California, Berkeley, and International Computer Science Institute

Abstract: 

As social networks emerge as an important tool for political engagement and dissent, services including Twitter and Facebook have become regular targets of censorship. In the past, nation states have exerted their control over Internet access to outright block connections to social media during times of political upheaval. Parties without such capabilities may however still desire to control political expression. A striking example of such manipulation recently occurred on Twitter when an unknown attacker leveraged 25,860 fraudulent accounts to send 440,793 tweets in an attempt to disrupt political conversations following the announcement of Russia’s parliamentary election results.

In this paper, we undertake an in-depth analysis of the infrastructure and accounts that facilitated the attack. We find that miscreants leveraged the spam-as-a-service market to acquire thousands of fraudulent accounts which they used in conjunction with compromised hosts located around the globe to flood out political messages. Our findings demonstrate how malicious parties can adapt the services and techniques traditionally used by spammers to other forms of attack, including censorship. Despite the complexity of the attack, we show how Twitter’s relevance-based search helped mitigate the attack’s impact on users searching for information regarding the Russian election.

 

Kurt Thomas, University of California, Berkeley, and Twitter

Chris Grier, University of California, Berkeley

Vern Paxson, University of California, Berkeley, and International Computer Science Institute

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

Thomas PDF
View the slides

Presentation Video

Presentation Audio

MP3 Download OGG Download

Download Audio

  • Log in or    Register to post comments

General Sponsors

© USENIX

  • Privacy Policy
  • Contact Us