http://hdl.handle.net/10900/163069 2026-07-04T01:31:12Z 2026-07-04T01:31:12Z Kaven, Sascha Volkmann, Moritz Skwarek, Volker http://hdl.handle.net/10900/163785 2025-04-04T01:12:30Z 2025-04-03T00:00:00Z

Assessing Effects of Cyber-Attacks on Smart Grids through Power Grid and Communication Co-Simulation Kaven, Sascha; Volkmann, Moritz; Skwarek, Volker The transition to renewable energy sources has led to the development of smart grids, which integrate advanced metering infrastructure and communication networks to enhance grid management. However, this evolution also introduces new cyber-attack surfaces. This paper presents a co-simulation tool designed to assess the impact of cyber-attacks on smart grids by simulating both power grid and communication components. Focusing on false data injection attacks, the tool evaluates the effects of manipulated measurement data on state estimation and grid stability. Initial results demonstrate the tool’s capability to identify vulnerabilities and inform the development of robust security measures for future smart grid control systems.

2025-04-03T00:00:00Z Bechtel, Lukas Schramm, Markus Popperl, Lukas Heer, Tobias http://hdl.handle.net/10900/163784 2025-04-04T01:02:29Z 2025-04-03T00:00:00Z

Scalable Cybersecurity Training: Integrating Virtual and Physical Security Teaching Environments Bechtel, Lukas; Schramm, Markus; Popperl, Lukas; Heer, Tobias The number of cybersecurity incidents increases year over year. Cybersecurity education requires hands-on experience to protect infrastructure and services against hackers. However, existing teaching infrastructures face scalability and hardware integration challenges. This paper presents a semivirtualized security teaching infrastructure combining virtual infrastructure, physical hardware access, and an Attack & Defense framework. The infrastructure is based on a Proxmox cluster, managed through a self-developed platform that allows parallel access to different courses. The teaching concept enables students to solve team-based exercises on personal laptops. Using personal laptops motivates students to create and maintain their own set of tools for cybersecurity analysis. Automated scoring and hardware interaction enhance engagement, providing a flexible platform for practical cybersecurity training.

2025-04-03T00:00:00Z Steinert, Benjamin Paradzik, Gabriel Menth, Michael http://hdl.handle.net/10900/163782 2025-04-04T01:02:31Z 2025-04-03T00:00:00Z

Automated Test Bench for High-Performance Network Equipment Steinert, Benjamin; Paradzik, Gabriel; Menth, Michael This paper presents an automated test bench that supports reproducible and holistic benchmarking of data plane and control plane performance. The modular architecture integrates the hardware-based traffic generator P4TG and the software-based traffic generator iperf3 for precise control over test traffic. Additionally, it supports automated Device under Test (DuT) reconfiguration between test runs and metric collection. A case study demonstrates the feasibility of the approach by measuring the performance of a modern P4-based COTS data center switch.

2025-04-03T00:00:00Z Zink, Etienne Flüchter, Moritz Lindner, Steffen Ihle, Fabian Menth, Michael http://hdl.handle.net/10900/163778 2025-04-04T01:12:33Z 2025-04-03T00:00:00Z

Rust Barefoot Runtime (RBFRT): Fast Runtime Control for the Intel Tofino Zink, Etienne; Flüchter, Moritz; Lindner, Steffen; Ihle, Fabian; Menth, Michael Data plane programming enables the programmability of network devices with domain-specific programming languages, like P4. One commonly used P4-programmable hardware target is the Intel Tofino™ switching ASIC. The runtime behavior of an implemented P4 program on Tofino™ can be configured with shell scripts or a Python library from Barefoot provided with the Tofino™. Both are limited in their capabilities and usability. In this paper, we introduce the Rust Barefoot Runtime (RBFRT), a Rust-based control plane library. The RBFRT provides a fast and memory-safe interface to configure the Intel Tofino™. We showed that the RBFRT achieves a higher insertion rate for MAT entries and has a shorter response time compared to the Python library.

2025-04-03T00:00:00Z