Self adaptive high interaction honeypots driven by game theory

Abstract

High-interaction honeypots are relevant to provide rich and useful information obtained from attackers. Honeypots come in different flavors with respect to their interaction potential. A honeypot can be very restrictive, but then only a few interactions can be observed. If a honeypot is very tolerant though, attackers can quickly achieve their goal. Having the best trade-off between attacker freedom and honeypot restrictions is challenging. In this paper, we address the issue of self adaptive honeypots, that can change their behavior and lure attackers into revealing as much information as possible about themselves. The key idea is to leverage game-theoretic concepts for the configuration and reciprocal actions of high-interaction honeypots. © 2009 Springer-Verlag Berlin Heidelberg.