  Since honeypots first appeared as an advanced network security concept they
suffer from poor deployment and maintenance strategies. State-of-the-Art
deployment is a manual process in which the honeypot needs to be configured and
maintained by a network administrator. In this paper we present a method for a
dynamic honeypot configuration, deployment and maintenance strategy based on
machine learning techniques. Our method features an identification mechanism
for machines and devices in a network. These entities are analysed and
clustered. Based on the clusters, honeypots are intelligently deployed in the
network. The proposed method needs no configuration and maintenance and is
therefore a major advantage for the honeypot technology in modern network
security.
