Research Group
Machine Learning
and Security
View from our building over Berlin.

Teaching

Summer 2025

We offer different Bachelor and Master courses that revolve around machine learning and computer security. Following is a list of all courses offered in the summer term 2025.

MLSEC — Machine Learning for Computer Security

This integrated lecture is concerned with using machine learning in computer security. Many tasks in security, such as the analysis of malicious software or the discovery of vulnerabilities, rest on manual work. Methods from machine learning can help accelerate this process and make security systems more intelligent. The lecture explores different approaches for constructing such learning-based security systems.

   Course Website    Module 41101 Type: Lecture Audience: Master

SECLAB — Applied Security Lab

This lab is a hands-on, entry-level course that explores the security analysis of systems. It provides an introduction to practical system security and serves a preparation for later advanced security labs. This includes developing strategies and tools for security analysis as well as investigating the security of real-world systems. In each unit of the lab, a different system is analyzed, ranging from Android applications to network hosts.

   Course Website    Module 41100 Type: Lab course Audience: Bachelor, Master

RAID — Reproducing AI Attacks and Defense

This project puts recent AI research to the test. Participants will re-implement current attack and defense techniques that utilize machine learning, evaluate their capabilities, and design improvements. Possible techniques include attacks and defenses for large language models and computer vision systems. The overall goal is to learn about the state of the art in AI security and reproduce results where possible.

   Course Website    Module 41102 Type: Project Audience: Master

SEPA — Security and Privacy of AI

This block seminar focuses on security and privacy in artificial intelligence and machine learning. We will examine recent attacks on learning algorithms and discuss their impact on practical security and privacy. We will also look at possible defenses and countermeasures to protect learning algorithms and the underlying data. The seminar is intended for Master students.

   Course Website    Module 41104 Type: Seminar Audience: Master

MOPS — Mobile Privacy and Security

This block seminar deals with the security and privacy of mobile devices. We will discuss different concepts for analyzing and detecting security threats, such as attacks and malicious software. Futhermore, we will explore defense strategies suitable for mobile environments. The seminar is intended for Bachelor students. A good understanding of computer security is required.

   Course Website    Module 41103 Type: Seminar Audience: Bachelor

Thesis Topics

Are you looking for an exciting topic for your Bachelor or Master thesis? Simply contact Prof. Rieck. Note that we do not have a list of "off the shelf" topics. Instead, we try to find interesting thesis topics together with the students that align with our current research.