Datalab: Intelligent Data Analysis for Computer Security


SemesterSummer 2024
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.


16. AprilKick-off (physical presence mandatory) &
Unit 0: An easy start
30. April and 07. MayUnit 1: Lots and Lots of Spam
14. May and 21 MayUnit 2: Network-based Attack Detection
28. May and 04. JunUnit 3: Embedded Malware
04. Jun and 11. JunUnit 4: Android Malware Detection
18. Jun and 25. JunUnit 5: Adversarial Machine Learning
02. Jul and 09. JulUnit 6: Model Stealing/Extraction
16. JulDeadline for the last unit
23. 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.