The research area Network Security focusses on creating a powerful scientific toolkit for studying the most pressing issues of future telecommunication networks: Security, Efficiency, Stability and Complexity Management. With the advent of the network disaggregation paradigm (most notably currently known under the ORAN initiative – Open Radio Access Networks), the resulting complexity of the networks and their management increases to such a degree that traditional deterministic engineering approaches dramatically falter. As a consequence, simulation tools that run on a high-definition digital representation of the network are needed. These are dubbed “Digital Twins”. We study how Digital Network Twins should be best set up to investigate various questions, ranging from network resource optimization to aggregate energy consumption optimization.

Security research in a telecommunication network context is a subject that scales with the complexity increase described above: the more complex the management of a network structure becomes, the more its attack surface is expanded. In our security research, we develop modern and automatized vulnerability scanning approaches for these complex networks. With the target picture of a powerful adaptable and overarching security analytics platform, we approach current infrastructure trends such as cloudification, and disaggregation. Furthermore, the recent revolutionary progress in Generative AI functionality opens up new perspectives in Network Security. We study novel concepts to support the security analyst with optimally tailored tools employing Generative AI.

Ultimately, Digital Network Twins should be able to bolster Network Security approaches that are able to render negative reaction times: potential attacks are recognized before they are devised and carried out. With this visionary aim in mind, we set up the R&D activities in our research field.