Stefan Marksteiner

Tanmay Khule, Stefan Marksteiner, Jose Alguindigue et al.

In modern automotive development, security testing is critical for safeguarding systems against increasingly advanced threats. Attack trees are widely used to systematically represent potential attack vectors, but generating comprehensive test cases from these trees remains a labor-intensive, error-prone task that has seen limited automation in the context of testing vehicular systems. This paper introduces STAF (Security Test Automation Framework), a novel approach to automating security test case generation. Leveraging Large Language Models (LLMs) and a four-step self-corrective Retrieval-Augmented Generation (RAG) framework, STAF automates the generation of executable security test cases from attack trees, providing an end-to-end solution that encompasses the entire attack surface. We particularly show the elements and processes needed to provide an LLM to actually produce sensible and executable automotive security test suites, along with the integration with an automated testing framework. We further compare our tailored approach with general purpose (vanilla) LLMs and the performance of different LLMs (namely GPT-4.1 and DeepSeek) using our approach. We also demonstrate the method of our operation step-by-step in a concrete case study. Our results show significant improvements in efficiency, accuracy, scalability, and easy integration in any workflow, marking a substantial advancement in automating automotive security testing methodologies. Using TARAs as an input for verfication tests, we create synergies by connecting two vital elements of a secure automotive development process.

Stefan Marksteiner, Benjamin Rainer, Oliver Maurhart

This paper presents a practical solution to the problem of limited bandwidth in Quantum Key Distribution (QKD)- secured communication through using rapidly rekeyed Internet Protocol security (IPsec) links. QKD is a cutting-edge security technology that provides mathematically proven security by using quantum physical effects and information theoretical axioms to generate a guaranteed non-disclosed stream of encryption keys. Although it has been a field of theoretical research for some time, it has only been producing market-ready solutions for a short period of time. The downside of this technology is that its key generation rate is only around 52,000 key bits per second over a distance of 50 km. As this rate limits the data throughput to the same rate, it is substandard for normal modern communications, especially for securely interconnecting networks. IPsec, on the other hand, is a well-known security protocol that uses classical encryption and is capable of exactly creating site-to-site virtual private networks. This paper presents a solution that combines the performance advantages of IPsec with QKD. The combination sacrifices only a small portion of QKD security by using the generated keys a limited number of times instead of just once. As a part of this, the solution answers the question of how many data bits per key bit make sensible upper and lower boundaries to yield high performance while maintaining high security. While previous approaches complement the Internet Key Exchange protocol (IKE), this approach simplifies the implementation with a new key synchronization concept, proposing a lightweight protocol that uses relatively few, slim control messages and sparse acknowledgement. Furthermore, it provides a Linux-based module for the AIT QKD software using the Netlink XFRM Application Programmers Interface to feed the quantum key to the IP***ABSTRACT TRUNCATED TO 1920 CHARS***

Stefan Marksteiner, Harald Lernbeiß, Bernhard Jandl-Scherf

As today's organizational computer networks are ever evolving and becoming more and more complex, finding potential vulnerabilities and conducting security audits has become a crucial element in securing these networks. The first step in auditing a network is reconnaissance by mapping it to get a comprehensive overview over its structure. The growing complexity, however, makes this task increasingly effortful, even more as mapping (instead of plain scanning), presently, still involves a lot of manual work. Therefore, the concept proposed in this paper automates the scanning and mapping of unknown and non-cooperative computer networks in order to find security weaknesses or verify access controls. It further helps to conduct audits by allowing comparing documented with actual networks and finding unauthorized network devices, as well as evaluating access control methods by conducting delta scans. It uses a novel approach of augmenting data from iteratively chained existing scanning tools with context, using genuine analytics modules to allow assessing a network's topology instead of just generating a list of scanned devices. It further contains a visualization model that provides a clear, lucid topology map and a special graph for comparative analysis. The goal is to provide maximum insight with a minimum of a priori knowledge.