Datalab: Intelligent Data Analysis for Computer Security


SemesterSummer 2023
Course typePractical Course/ Lab
LecturerJun.-Prof. Dr. Wressnegger
AudienceInformatik Master & Bachelor
Credits4 ECTS
Room148, Building 50.34


In this practical course, the students develop learning-based systems for different computer security tasks, thereby intensifying their knowledge gained in the lecture "Machine Learning for Computer Security."

The students have the unique opportunity to design, implement, and evaluate systems based on real-world data used in computer security research.

The "Datalab" is composed of 6 units with several individual tasks covering different topics from classical computer security research, such as attack detection, spam classification, or vulnerability discovery. In each unit, the students develop an approach, train and validate it on known data, and submit their solution to the course platform, where the approach is tested against unknown data.

The best approaches are awarded at the end of the semester and presented at a joint colloquium and get-together.


18. AprilKick-off (physical presence mandatory) &
Unit 0: An easy start
25. AprilUnit 1: Lots and Lots of Spam
02. May and 09. MayUnit 2: Network-based Attack Detection
16. May and 23. MayUnit 3: Embedded Malware
06. Jun and 13. JunUnit 4: Android Malware Detection
20. Jun and 27. JunUnit 5: Adversarial Machine Learning
04. Jul and 11. JulUnit 6: Model Stealing/Extraction
18. JulDeadline for the last unit
25. JulAward ceremony and presentation at final colloquium


To participate it is strongly recommended to have attended the lecture

Matrix Chat

News about the practical course, potential updates to the schedule, and additional material are distributed using the course's matrix room. Moreover, matrix enables students to discuss topics and solution approaches.

You find the link to the matrix room on ILIAS.

You find the link to the matrix room on ILIAS.