This survey is part of the discipline Experimental Software Engineering, offered on the Universidade Federal de Sergipe, as part of the requirements for the MsC in Computer Science.

The objective of this survey is to identify the most important areas where Machine Learning techniques can be applied to IDS (Intrusion Detection System) alerts, so that security analysts can be more productive.

In this respect, we see the following areas where machine learning can be applied:

* Detection of new/unknown threats
* Generation of fewer false positives
* Better grouping of related informations
* Prioritize the most important alerts
* Better correlation between alerts/logs entries

We would like to know which ones you (the IDS analyst) find to be the most important.

We intend to make this data public after our initial analysis. If you want to be informed when this happens, please fill your in e-mail while answering the survey.

Thank you for your participation.