The Mobile Security Group was established in 2014 at the Faculty of Electrical Engineering and Information Technology and is part of the Horst-Görtz-Institute for IT-Security (HGI). The group is headed by Prof. Dr. Markus Dürmuth.
News
Teaching in winter term
21.09.2018 - Maximilian Golla
This winter term we contribute to the new lecture Introduction to Usable Security and Privacy for Bachelor students. Furthermore, we offer the lecture Methods of User Authentication, as well as, the new Practical Course on Usable Security and Privacy for Master students.
Teaching in summer term
21.03.2018 - Theodor Schnitzler
This summer term we offer the lecture Usable Security and Privacy. Note that this course will start in the third week, the first lecture is scheduled for Tuesday, 24 April 2018.
Furthermore, we offer the Master-Seminar Human Centered Security and Privacy, and we contribute to the lecture IT-Sicherheit für Geistes- und Gesellschaftswissenschaften.
Usability of Risk-based Implicit Authentication
07.06.2017 - Markus Duermuth
Our project Usability of Risk-based Implicit Authentication will receive funding through the North Rhine-Westphalian Graduate School “Human Centered Systems Security” (NERD NRW). The project studies the security and usability of so-called risk-based authentication, an additional layer that improves the security and usability of “traditional” password-based authentication. Also involved in the project is the Data & Application Security Group at TH Cologne.
We are looking for a highly qualified and motivated PhD student to work on the project. If you are interested please contact Prof. Dr. Dürmuth.
Teaching in summer term
13.04.2017 - Markus Duermuth
This summer term we offer the lecture Usable Security and Privacy and the Master-Seminar Security and Privacy of Wireless Networks and Mobile Devices.
Furthermore, we contribute to the lecture IT-Sicherheit für Geistes- und Gesellschaftswissenschaften.
Release of OMEN - A Markov Model-Based Password Guesser
15.03.2017 - Maximilian Golla
OMEN is a Markov model-based password guesser written in C. It generates password candidates according to their occurrence probabilities, i.e., it outputs most likely passwords first. If you are interested in the details on how OMEN improves on existing Markov model-based password guessing approaches, please refer to OMEN: Faster Password Guessing Using an Ordered Markov Enumerator.
You can download OMEN from GitHub.