Title: SocioBot: a Twitter-based botnet

 

Author: Ismeet Kaur Makkar; Fabio Di Troia; Corrado Aaron Visaggio; Thomas H. Austin; Mark Stamp

 

Addresses:
Department of Computer Science, San Jose State University, One Washington Square, San Jose, CA 95192, USA
Department of Engineering, Università degli Studi del Sannio, Via Traiano, 3, Benevento BN, Italy
Department of Engineering, Università degli Studi del Sannio, Via Traiano, 3, Benevento BN, Italy
Department of Computer Science, San Jose State University, One Washington Square, San Jose, CA 95192, USA
Department of Computer Science, San Jose State University, One Washington Square, San Jose, CA 95192, USA

 

Journal: Int. J. of Security and Networks, 2017 Vol.12, No.1, pp.1 - 12

 

Abstract: A botnet is a collection of computers controlled by a botmaster, often used for malicious activity. Social media provides an ideal platform for controlling a botnet, and also an avenue for botnets to spread their reach. In this research, we develop a botnet, SocioBot, that uses Twitter for its command and control (C&C) system. We conduct a variety of simulations based on this botnet. Epidemic models are used to validate and analyse our botnet simulations.

 

Keywords: malware; epidemic models; Twitter based botnets; stochastic simulation; social media; social networks.

 

DOI: http://dx.doi.org/10.1504/IJSN.2017.10001803

 

 

Editors Full Text AccessAccess for SubscribersPurchase this articleComment on this article