Statistical classification of services tunneled into SSH connections by a K-means based learning algorithm

  • Authors:
  • G. Maiolini;A. Baiocchi;A. Rizzi;C. Di Iollo

  • Affiliations:
  • Elsag Datamat SpA, Rome, Italy;University of Rome, Sapienza, Rome;University of Rome, Sapienza, Rome;Elsag Datamat SpA, Rome, Italy

  • Venue:
  • Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
  • Year:
  • 2010

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Abstract

Secure SHell is a TCP based protocol designed to enhance with security features telnet and other insecure remote management tools. Due to its versatility, it is often exploited to forward applications (i.e. HTTP, SCP, etc.) into encoded TCP traffic flows. The point which makes challenging the identification of the uses of SSH is that packets are enciphered and instruments based on deep packet inspection (DPI) cannot achieve this task. We approached the problem of early SSH classification with k-means based machine by studying statistical behavior of IP traffic parameters, such as length, arrival time and direction of packets. In this paper we describe tools and networks designed to collect SSH remote administration traffic as well as relevant results obtained for its classification. In particular, our tool identifies remote management traffic out of other SSH encoded applications with accuracy up to 90.34