Echeverria, Juan;
Besel, Christoph;
Zhou, Shi;
(2018)
Discovery of the Twitter Bursty Botnet.
In: Heard, Nick and Adams, Niall and Rubin-Delanchy, Patrick and Turcotte, Melissa, (eds.)
Data Science for Cyber-Security.
(pp. pp. 145-159).
World Scientific Publishing: Singapore, Singapore.
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Abstract
Many Twitter users are bots. They can be used for spamming, opinion manipulation and online fraud. Recently, we discovered the Star Wars botnet, consisting of more than 350,000 bots tweeting random quotations exclusively from Star Wars novels. The bots were exposed because they tweeted uniformly from any location within two rectangle-shaped geographic zones covering Europe and the USA, including sea and desert areas in the zones. In this chapter, we report another unusual behaviour of the Star Wars bots, that the bots were created in bursts or batches, and they only tweeted in their first few minutes since creation. Inspired by this observation, we discovered an even larger Twitter botnet, the Bursty botnet with more than 500,000 bots. Our preliminary study showed that the Bursty botnet was directly responsible for a large-scale online spamming attack in 2012. Most bot detection algorithms have been based on assumptions of “common” features that were supposedly shared by all bots. Our discovered botnets, however, do not show many of those features; instead, they were detected by their distinct, unusual tweeting behaviours that were unknown until now.
| Type: | Proceedings paper |
|---|---|
| Title: | Discovery of the Twitter Bursty Botnet |
| Event: | Data Science for Cyber-Security 2017 |
| Location: | London |
| ISBN-13: | 978-1-78634-563-9 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1142/9781786345646_007 |
| Publisher version: | https://doi.org/10.1142/9781786345646_007 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10161759 |
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