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.
CARE — Code Analysis and Reverse Engineering
This block seminar is concerned with the analysis and reverse engineering of code. We will cover different techniques for program analysis of source code and binary code. In addition, we will look at concepts for understanding unknown software, reverse engineering its functionality, and discovering security vulnerabilities. The seminar is intended for Master students.
PASIL — Privacy and Security in Learning
This block seminar focuses on privacy and security in machine learning. We will examine recent attacks on learning algorithms and discuss their impact on privacy and security. We will also look at possible defenses and countermeasures to protect machine learning. The seminar is intended for Bachelor students. However, a basic understanding of machine learning is recommended.