Datalab: Intelligent Data Analysis for Computer Security

Overview

SemesterWinter 2021
Course typePractical Course/ Lab
LecturerJun.-Prof. Dr. Wressnegger
AudienceInformatik Master & Bachelor
Credits4 ECTS
Time14:00–17:15
Room149, Building 50.34 and online
LanguageEnglish
Linkhttps://ilias.studium.kit.edu/goto_produktiv_crs_1600113.html
RegistrationPlease register for the course in ILIAS

Remote Course

Due to the ongoing COVID-19 pandemic, this course is going to start off remotely, meaning, the kick-off meeting and the individual units will happen online. The final colloquium, however, will hopefully be an in-person meeting again (<- This time we might indeed have a chance).

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Description

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.

Schedule

DateStep
26. OctKick-off &
Unit 0: An easy start
2. Nov and 9. NovUnit 1: Lots and Lots of Spam
16. Nov and 23. NovUnit 2: Network-based Attack Detection
30. Nov and 7. DecUnit 3: Embedded Malware
14. Dec and 21. DecUnit 4: Adversarial Machine Learning
11. Jan and 18. JanUnit 5: Android Malware Detection
25. Jan and 12. JanUnit 6: Bot Detection on Social Media
08. FebAward ceremony and presentation at final colloquium

Prerequisites

To participate it is strongly recommended to have attended the lecture

or the lectures

Mailing List

News about the practical course, potential updates to the schedule, and additional material are distributed using a separate mailing list. Moreover, the list enables students to discuss topics and solution approaches.

You can subscribe here.