Research Group
Machine Learning
and Security
and Security
View from our building over Berlin.
We offer a number of courses each semester that revolve around machine learning and security. These include lectures on learning algorithms in security systems and adversarial machine learning as well as our labs where people can experiment with attacks and malicious code. Teaching is fun for us and so we have been able to even win awards for our lectures and practical courses.
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.
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.
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.
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.
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.
Below is a list of all the courses we have offered in recent years. Note that some courses are not offered regularly, while others are planned and not yet available. Please consult the respective pages on the ISIS platform of TU Berlin.
Are you looking for an exciting topic for your Bachelor or Master thesis? We offer research-oriented thesis topics on machine learning and security, which we design together with the students. Contact Prof. Rieck by email and ask for further details. Please include the result of (23**42)%2248 in the subject line.
