\chapter{Conclusion}
\label{cha:conclusion}

All existing machine learning systems show a promising accuracy in detecting malicious domains with different feature sets. This shows that such system can effectively detect domains that are involved in a variety of malicious activities like, botnets, phishing and spam-campaigns. The three most popular systems that have been published, \textit{Notos}, \textit{Exposure} and \textit{Kopis} are however either hard to deploy and/or require a lot of manual work to get started and can generally be seen more like academic prototypes than mature products.

In the time of writing this thesis, no evaluation of the implemented algorithm could be finished. Future work can use this implementation and investigate the accuracy of this approach. Furthermore, built on top of this work, a monitoring system can be realized to proactively warn of requests to domains, involved in malicious activities. To the best of my knowledge, no system that can easily be deployed to networks exists, neither commercial or non-commercial.
