| Semester | Summer 2023 |
| Course type | Practical Course/ Lab |
| Lecturer | TT.-Prof. Dr. Wressnegger |
| Audience | Informatik Master & Bachelor |
| Credits | 4 ECTS |
| Time | 14:00–17:15 |
| Room | 148, Building 50.34 |
| Language | English |
| Link | TBA |
| Registration | https://ilias.studium.kit.edu/goto.php?target=crs%5F2081076&client_id=produktiv |
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
The best approaches are awarded at the end of the semester and presented at a joint colloquium and get-together.
| Date | Step |
| 18. April | Kick-off (physical presence mandatory) & Unit 0: An easy start |
| 25. April | Unit 1: Lots and Lots of Spam |
| 02. May and 09. May | Unit 2: Network-based Attack Detection |
| 16. May and 23. May | Unit 3: Embedded Malware |
| 06. Jun and 13. Jun | Unit 4: Android Malware Detection |
| 20. Jun and 27. Jun | Unit 5: Adversarial Machine Learning |
| 04. Jul and 11. Jul | Unit 6: Model Stealing/Extraction |
| 18. Jul | Deadline for the last unit |
| 25. Jul | Award ceremony and presentation at final colloquium |
To participate it is strongly recommended to have attended the lecture
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.