PEOPLE PARTNERS PROJECTS APPLY PROGRAM
The SecInt doctoral college at TU Wien aims to develop the scientific foundations of secure and intelligent human-centric digital technologies. To achieve this goal, SecInt will fund 10 PhD positions.

The application to the SecInt doctoral college is open from October 8th to November 30th. Find out how to apply here!

Digitalization is transforming our society, making our everyday life more and more dependent on computing platforms and online services. These are built so as to sense and process the environment in which we live as well as the activities we carry on, with the ultimate goal of returning predictions and taking actions to support and enhance our life. Prominent examples are

  • Autonomous systems (e.g., self-driving cars and robots),
  • Cyber-physical systems (e.g., implanted medical devices),
  • Apps in wearable devices (e.g., Coronavirus contact tracing apps).

Despite the interest of stake holders and the attention of media, digital technologies that so intimately affect the human life are not yet ready for widespread deployment, as key technical and ethical questions, such as trustworthiness, security, and privacy, are open. If these problems are not solved, supposedly intelligent human-centric technologies can lead to undesirable consequences or even death: e.g.,

  • Learning algorithms of autonomous cars can be fooled so as to cause crash accidents,
  • Implanted medical devices can be remotely hacked to trigger unwanted defibrillations,
  • Contact tracing apps can be misused towards an Orwellian surveillance system or to inject false at-risk alerts.

The goal of SecInt is to develop the scientific foundations of secure and intelligent human-centric digital technologies. This requires interdisciplinary research, establishing synergies between different research fields (Security and Privacy, Machine Learning, and Formal Methods). Research highlights include

  • Design of machine learning algorithms resistant to adversarial attacks,
  • Design of machine learning algorithms for security and privacy analysis,
  • Security analysis of personal medical devices,
  • Design of secure and privacy- preserving contact tracing apps,
  • Enforcement of safety for dynamic robots.

The research development is accompanied by a supporting educational and training programme, which encompasses the ethics of secure and intelligent digital technologies, interdisciplinary technical knowledge, as well as internships in international elite research partners, which expressed interest to collaborate with SecInt.