Protecting and monitoring critical infrastructure

IntelPlaMo

The IntelPlaMo project addresses a central challenge of modern security infrastructure, which is essentially based on a lack of robust data infrastructure and insecure sensor links: Critical systems such as airports or train stations require reliable surveillance, but the safe and autonomous use of drones (UAS) is still a technologically incompletely solved risk. The current state of the art has significant deficits, as there are no mechanisms to guarantee autonomous flight operations under adverse conditions - such as cyber attacks, system failures or other critical scenarios - in a data-secure manner.
Without a robust data infrastructure and effective on-device security mechanisms, the use of drone-based surveillance technologies remains risky and cannot be fully utilized. In addition, existing ground and airborne sensor data is often not linked efficiently or securely to create a comprehensive picture of the situation.

Drohne
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As part of the project, our Institute of Data Science is providing concrete solutions to close these gaps by contributing expertise in the areas of stakeholder analysis, domain-based data evaluation for situational awareness and software security. Specifically, our contributions include the following:

    • Developing a concept for testing and evaluating new automated components of a digital control center.
    • Use of 3D information from structure-from-motion point clouds for status analysis and automated change detection.
    • Continuous, automated analysis of potential threats to information security within the software platform.

The concrete benefit for society and authorities lies in well-founded decision support for organizations with security tasks. The methods developed are validated in practical tests at real locations. In this way, we make an important contribution to the security of critical infrastructures against failures and attacks as well as to the condition monitoring of these systems. By validating scalable solutions, we are also strengthening DLR's position in application-oriented drone research.

Project duration: 01/2026 - 12/2028

Participating institutes and facilities

Institute of Flight Guidance

The Institute of Flight Guidance in Braunschweig is working on the development and application of future processes and technologies for the integrated airborne and ground-based guidance of aircraft.

Institute of Flight Systems

The DLR Institute of Flight Systems has been active in the topics of flight mechanics and measurement and system technology of all flying systems at the DLR site Braunschweig since 1953.

Institute for AI Safety and Security

At the Institute for AI Safety & Security, we research and develop on both our sites in Sankt Augustin and in Um, AI-related methods, processes, algorithms, technologies and execution and system environments. Our focus is on safe and standard-compliant AI, cyber security in open data and service ecosystems and AI, as well as autonomous mobility and logistics facilitation.

Institute of Software Methods for Product Virtualization

The Institute for Software Methods for Product Virtualisation researches and develops the technical basis for generating virtual products in aviation.

Institute of Systems Engineering for Future Mobility

The newly founded DLR Institute of Systems Engineering for Future Mobility in Oldenburg focuses on research into the methods needed to develop and validate future automated and autonomous transport systems.

Institute of Transportation Systems

The DLR Institute of Transportation Systems, with sites in Braunschweig and Berlin, conducts research and focuses on automotive and rail systems, as well as transport and mobility management, with a view to shaping the way people travel and goods are transported.

Institute of Data Science

The DLR Institute of Data Science develops methods to extract knowledge from data, generate innovation, and enable data-driven decisions. It aims at a comprehensive "data backbone" by considering the entire data lifecycle. It thus promotes an efficient and innovative use of data in science and society by strengthening sustainable processes and technologies in all DLR application areas.