Machine Learning
and Security
Website of the
Chair of Machine Learning and Security
View from our building over Berlin.


Summer 2023

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.

Type: Integrated Lecture Audience: Master Module: #41101

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.

Type: Practical course Audience: Bachelor Module: #41100

CARE — Code Analysis and Reverse Engineering

This block seminar is concerned with code analysis and reverse engineering. We will cover different techniques for program analysis of source code and binary code. Moreover, we will look at concepts for understanding unknown code and discovering security vulnerabilities.

Type: Seminar Audience: Master Module: #41104

PASIL — Privacy and Security in Learning

This block seminar deals with privacy and security in machine learning. We will investigate recent attacks against learning algorithms and discuss their impact on privacy and security. We will also look at possible defenses and countermeasures suitable for protecting learning.

Type: Seminar Audience: Bachelor Module: #41103