Improved self adaptive honeypots capable of detecting rootkit malware
Adrian Pauna · 2012
The latest trends in the development of high interaction honeypots show that adaptive honeypots, which lure attackers by changing their behavior, are a feasible solution for gathering of as much information as possible about them. Adaptive Honeypot systems based on Game theory are in a development stage and the systems created until now are focused mostly on applying game-theoretic concepts for the configuration and reciprocal actions of high-interaction honeypots [1]. The paper presents a tested proof of concept system that integrates dynamic taint analysis with an existing adaptive honeypot in order to detect the rootkit malware that the attacker installs.