Applied Security & Data Science

Applied Security, in our understanding, comprises above all the detachment from purely theoretical and software-oriented aspects to the safeguarding of real (complex) systems, which have to fulfil corresponding framework parameters (e.g. uptime, immutability, certifications).

A special focus of this topic for us lies in the area of industrial security, which is of particular importance with regard to complexity and criticality: Due to the increasing interconnection of industrial systems (operational technology, OT), also with the Internet and external applications, and the use of standard IT components, security risks similar to those in the Internet world are occurring more and more frequently in the industrial environment.

The Stuxnet malware has impressively shown that even sealed automation systems can be attacked. Since then, industrial components as well as industrial systems have become increasingly targeted by attackers.

Data Science

Data Science is another thematic focus of our institute's research work, not least with regard to the use of our research work in the new course of studies "Data Science & Business Analytics". The current focus lies on the interface between data science and IT security, especially privacy: Privacy Aware Machine Learning and data protection are only two aspects. We are particularly concerned with how this contradiction between the highest possible data protection on the one hand and the highest possible data utility on the other can be resolved, but also with the proactive and reactive protection of data in data-driven applications (e.g. data leak detection). For us, however, data science is also an enabler in terms of researching new methods to increase security, such as automated malware detection or traffic analysis.

In addition, we also have experience in the application of machine learning methods, which we are happy to make available in cooperation projects with use-case providers.

Key Focus Coordinator

  • Senior Researcher
    Josef Ressel Center for Unified Threat Intelligence on Targeted Attacks
  • Department of Computer Science and Security
P: +43/2742/313 228 690

Research Staff

  • Teaching and Research Assistant IT Security (BA)
  • Department of Computer Science and Security
  • Researcher
  • Department of Computer Science and Security
P: +43/2742/313 228 692
  • Lecturer
  • Deputy Academic Director Information Security (MA)
  • Department of Computer Science and Security
P: +43/676/847 228 634
  • Head of Research Institute
    Institute of IT Security Research
  • Lecturer
  • Head of Josef Ressel Center for Blockchain-Technologies and Security management
  • Department of Computer Science and Security
P: +43/676/847 228 696
  • Researcher IT Security (BA)
  • Department of Computer Science and Security
P: +43/2742/313 228 691
  • Junior Researcher Institute of IT Security Research
  • Department of Computer Science and Security



Secret Key Generation for Long Range Communication Networks - LoRaKey aims at energy efficient secret key generation for lightweight LPWAN applications.

Substation Security

The project aims at improving security within the automation network of power distribution systems by developing anomaly detection algorithms for the communication networks of substations.


Investigating threats to cyber-physical systems (CPS) and developing countermeasures