Volume 2 - Issue 1
Detecting Anomalies in Active Insider Stepping Stone Attacks
- Giovanni Di Crescenzo
Telcordia Technologies Piscataway, NJ, USA
giovanni@research.telcordia.com
- Abhrajit Ghosh
Telcordia Technologies Piscataway, NJ, USA
aghosh@research.telcordia.com
- Abhinay Kampasi
Microsoft Redmond, WA, USA
abhinay.kampasi@microsoft.com
- Rajesh Talpade
Niksun Princeton, NJ, USA
rtalpade@niksun.com
- Yin Zhang
University of Texas at Austin Austin, TX, USA
yzhang@cs.utexas.edu
Keywords: Network attackers, Journal of Wireless Mobile Networks, Ubiquitous Computing, Dependable Applications
Abstract
Network attackers frequently use a chain of compromised intermediate nodes to attack a target
machine and maintain anonymity. This chain of nodes between the attacker and the target is called
a stepping stone chain. Various classes of algorithms have been proposed to detect stepping stones,
timing correlation based algorithms being a recent one that is attracting significant research interest.
However, the existing timing based algorithms are susceptible to failure if the attacker actively tries
to evade detection using jitter or chaff. We have developed three anomaly detection algorithms to
detect the presence of jitter and chaff in interactive connections, based on response time, edit distance
and causality. Experiments performed on Deter using real-world traces and live traffic demonstrate
that the algorithms perform well with very low false positives and false negatives and have a high
success percentage of about 99%. These algorithms based on response times from the server and
causality of traffic in both directions of an interactive connection have made the existing stepping
stone detection framework more robust and resistant to evasion.