Registration for this course is open until Monday, 03.11.2025 23:59.

News

Change of Location for the First Tutorial – Now in E1 3, Lecture Hall HS002

Written on 28.10.25 by Christoph Landolt

Our first tutorial will take place tomorrow, 29.10.2025, from 16:15 to 17:45.
The goal of this session is to review Python programming and machine learning basics, and to set up the programming environment for the upcoming lessons.

Due to the high number of participants, the tutorial will now be… Read more

Our first tutorial will take place tomorrow, 29.10.2025, from 16:15 to 17:45.
The goal of this session is to review Python programming and machine learning basics, and to set up the programming environment for the upcoming lessons.

Due to the high number of participants, the tutorial will now be held in E1 3 – Lecture Hall HS002. The session will be passively streamed via Zoom for those who wish to follow it online.

All resources for the first tutorial are available here:
👉 https://christophlandolt.com/mlcysec_notebooks/

We’re looking forward to seeing you in the tutorial!

ML Recap Slides online

Written on 22.10.25 by Mario Fritz

Slides for the ML Recap are online.

While you are required to be familiar with ML/AI, we will go through some terminology so that we are on the same page and discuss a few specifics.

First Tutorial next week

Written on 22.10.25 by Mario Fritz

Quick reminder that today there is no tutorial yet.

The first tutorial will take place next week October 29th and you can find a tentative list of the tutorial classes on the following web page:

https://christophlandolt.com/mlcysec_notebooks/
(page is under construction)

Written on 17.10.25 by Mario Fritz

Given the number of students who attend the lecture in person, we will for now move back to the CISPA lecture hall (Stuhlsatzenhaus 5). This is the lecture hall we also had the first lecture.

PDF and video of the first introductory lecture are now available online on the internal page.

Please… Read more

Given the number of students who attend the lecture in person, we will for now move back to the CISPA lecture hall (Stuhlsatzenhaus 5). This is the lecture hall we also had the first lecture.

PDF and video of the first introductory lecture are now available online on the internal page.

Please note that the lecture will have a written exam at the end. For exact details on the logistics, we ask for your patience for about 1 week.

Reminder: Change of location

Written on 15.10.25 by Mario Fritz

Due to the exceptionally high number of registrations, the lecture is moved to E1 3 - Lecture Hall HS002. 

Machine Learning in Cybersecurity

Registration is now open!
Please register on this site in order to get access to material and stay in touch.

 

Recent advances in Machine Learning have led to strong performance in a wide range of tasks which led to a wide spread deployement roll out of such systems. ChatGPT and CoPilots for code and office applications just being a few prominent examples. In terms of privacy and security, this is a double-edged sword. ML techniques can be used to efficiently detect and prevent attacks (e.g., intrusion detection). However, their deployment to many real-world sensitive systems (e.g., self-driving cars, the cloud) also makes them susceptible to numerous attacks. As AI and ML becomes part of our IT infrastructure, we have to know and defend against cybersecurity threats. Recent uplift studies and use of AI in Capture the Flag Challenges have shown that the impact of agentic AI on the cybersecurity landscape will be significant. We will also discuss some of these latest developments.

The course explores in-depth both of these sides to Machine Learning and Cyber Security. The content addresses the following areas:

  1. Short ML recap
  2. ML for improving security
  3. Attacks on ML
  4. Defenses for ML
  5. Security of Large Language Models
  6. AI for CTF
  7. Impact of AI on Cybersecurity

 

Logistics:

  • Lectures will be on Thursdays 8:30am to 10am

  • Location: CISPA Lecture Hall, Stuhlsatzenhaus 5

  • First lecture on October 16th

  • Tentative date for exercise/tutorial classes: Wednesdays 4:15pm to 5:45pm (will start ~ 2 weeks after the lecture)

  • Modalities:

    • In person
    • Zoom
    • Video recording

Prerequisits

While we do a very brief recap in the beginning, the course requires knowledge on Machine Learning!

Material

Once you have registered - you have access to the internal pages with further information / material (under construction).

Privacy Policy | Legal Notice
If you encounter technical problems, please contact the administrators.