Hot Topics in Machine Learning for Computer Security

Overview

SemesterSummer 2026
Course typeBlock Seminar
LecturerProf. Dr. Wressnegger
AudienceInformatik Master & Bachelor
Credits4 ECTS
Room148, Building 50.34
LanguageEnglish
LinkTBA
Registrationhttps://ilias.studium.kit.edu/ilias.php?baseClass=ilrepositorygui&cmdNode=xu:m6&cmdClass=ilObjCourseGUI&cmd=view&ref_id=2904294

Description

This seminar is concerned with the combination of machine learning and computer security in practice. Many tasks in the security landscape are based on manual labor, such as searching for vulnerabilities or analyzing malware. Here, machine learning can be used to establish a higher degree of automation, providing more "intelligent" security solutions.

The module intensifies the contents of the MLSEC lectures, putting focus on timely topics from recent research. It teaches students to work up results from state-of-the-art research. To this end, the they will read up on a sub-field, prepare a seminar report, and present their work at the end of the term to their colleagues.

Schedule

DateStep
Wed, 22. Apr, 9:45–11:30Kick-off & Topic presentation
Thurs, 23. Apr, 11:59 (noon)Send topic selection
(assignment happens till 15:00)
Fri, 24. Apr, 11:59 (noon)Officially register for assigned topic
(missed opportunities will be reassigned to waiting list till 15:00)
Tue, 28. AprilOptional unit on "How to Ace the Seminar" (Online)
Thu, 30. AprilArrange appointments with assistant
Mon, 11. May - Fr, 15. May1st individual meeting (Provide first overview and ToC)
Mon, 8. Jun - Fr, 12. Jun2nd individual meeting (Feedback on draft report)
Wed, 1. JulSubmit final paper
Mon, 13. JulSubmit review for fellow students
Tue, 15. Jul, 13:30–16:00PC discussion meeting
Thu, 23. JulSubmit camera-ready version of your paper
Tue, 28. JulPresentation at final colloquium

Matrix Chat

News about the seminar, potential updates to the schedule, and additional material are distributed using the course's matrix room. Moreover, matrix enables students to discuss topics and solution approaches.

You find the link to the matrix room on ILIAS.

Topics

Every student may choose one of the following topics. For each of these, we additionally provide recent top-tier publications that serve as the basis for the seminar report. For the seminar and your final report, you should not merely summarize these papers, but try to go beyond and arrive at your own conclusions.

  • AI-based Source Code Analysis and Vulnerability Detection

  • AI-based Binary Code Analysis

  • LLM-based Automated Vulnerability Repair

  • Learning-based Android Malware Detection

  • Machine Learning for Network Intrusion / Anomaly Detection

  • LLM-Assisted Fuzzing

  • Concept Drift in Malware Detection

  • Visual Anomaly Detection