In information security domain, anomaly detection gains its own importance from researchers day by day. It is discovered that occasionally emerged frauds or intrusions in modern information systems have incurred significant loss when the suspicious activities were not detected or inefficiently processed. Therefore, numerous efforts have been devoted to devise effective detection methods, and then proceed to automation of anomaly identification in real time.
In this practical course, we challenge students with a set of well designated learning tasks, which require the participants to understand the task scenario entirely and to design their own algorithms to identify corresponding anomalies.
The competition on discovering the anomalies will be conducted based on the performance of their algorithms.
Contacts
![TUM logo](https://storage.googleapis.com/kaggle-media/competitions/inclass/3785/media/TUMLogo_mZlu_Vollfl_blau_RGB.png)
Department of computer science, Chair of IT Security
See details in
[ADCG SS'14 Homepage](http://ml.sec.in.tum.de/adcg)
Acknowledgements
We thank
[Prof.Dr.Claudia Eckert](http://www.sec.in.tum.de/claudia-eckert/)
for supporting us on this practical course.