Using Unsupervised Machine Learning to Detect Peer-to-Peer Botnet Flows

  • Andrea E. Medina Paredes
  • Yuan-Yuan Su
  • Wei Wu
  • Hung-Min Sun

Abstract

The war against botnet infection is fought every day by users that want to feel safe against any threat of compromise hosts. In this paper we are going to focus on the behavior of Peer 2 Peer (P2P) botnets, which along with hybrid botnets is a growing trend among attackers. The main approach will consist of a behavior comparison among features extracted from network flows, focusing only in the flows from P2P applications including P2P botnets.

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Published
2016-08-01
How to Cite
Paredes, A. E. M., Su, Y.-Y., Wu, W., & Sun, H.-M. (2016). Using Unsupervised Machine Learning to Detect Peer-to-Peer Botnet Flows. Proceedings of Engineering and Technology Innovation, 3, 28-30. Retrieved from http://ojs.imeti.org/index.php/PETI/article/view/238
Section
Articles