Machine Learning in Cybersecurity Mario Fritz

News

26.11.2021

Third task is online

The recording of today's tutorial and the third task are now uploaded.

Due date: 9th December 2021, 23:59:59

I wish you a great weekend!

17.11.2021

No tutorial session this week.

Hello, 

We would like to remind you that there is no exercise session this week. 

We will be back next week (26th Nov.), with Task 3 handout. 

Best,

Sahar

 

12.11.2021

Second task is online

The material of today's tutorial and the second task are now uploaded.

Due date: 25h November 2021, 23:59:59

I wish you a great weekend!

29.10.2021

First task is online.

The material of today's tutorial and the first task are now uploaded.

Due date: 11th November 2021, 23:59:59

27.10.2021

Second Tutorial on Fri 29.10.21 at 2:15pm

The second Tutorial will be on Friday, 29.10.2021 at 2:15pm. In this tutorial, we will have an introduction to Machine Learning with Python and will introduce the first exercise. The Zoom link and schedule can be found at ... Weiterlesen

The second Tutorial will be on Friday, 29.10.2021 at 2:15pm. In this tutorial, we will have an introduction to Machine Learning with Python and will introduce the first exercise. The Zoom link and schedule can be found at https://cms.cispa.saarland/mlcysecws2122/2 

20.10.2021

First Exercise on Fri 22.10.21 at 2:15pm

The first exercise will be on Friday, 22.10.2021 at 2:15pm. The Zoom link and schedule can be found at https://cms.cispa.saarland/mlcysecws2122/2 (registration required).

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Machine Learning in Cyber Security

Recent advances in Machine Learning has lead to near (or beyond) human-level performance in many tasks - autonomous driving, voice assistance, playing a variety of games. 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, such as introducing imperceptible perturbations in inputs and forcing ML systems behave in unintended ways.

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

  1. ML overview
  2. ML for improving security
  3. Attacks on ML
  4. Defenses for ML
  5. ML and Privacy

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

Date for lecture: Tuesdays noon to 2pm. 

Date for exercise: Fridays 2pm to 4pm

Due to the size of the course - the lecture will start in an online format until further notice.

The course requires prior knowledge on Machine Learning.

Once you have registered - please find internal information and schedule and links here (under construction).



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