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  • 1.
    Marksteiner, Stefan
    Mälardalen University, School of Innovation, Design and Engineering. AVL List GmbH.
    Model-Driven Security Test Case Generation Using Threat Modeling and Automata Learning2024Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Automotive systems are not only becoming more open through developments like advanced driving assistance functions, autonomous driving, vehicle-to-everything communication and software-defined vehicle functionality, but also more complex. At the same time, technology from standard IT systems become frequently adopted in this setting. These developments have two negative effects on correctness and security: the rising complexity adds potential flaws and vulnerabilities while the increased openness expands attack surfaces and entry points for adversaries. To provide more secure systems, the amount of verifying system security through testing has to be significantly increased, which is also a requirement by international regulation and standards. Due to long supply chains and non-disclosure policies, verification methods often have to operate in a black box setting. This thesis strives therefore towards finding more efficient methods of automating test case generation in both white and black box scenarios. The focus lies on communication protocols used in vehicular systems. The main approaches used are model-based methods. We provide a practical method to automatically obtain behavioral models in the form of state machines of communication protocol implementations in real-world settings using automata learning. We also provide a means to automatically check these implementation models for their compliance with a specification (e.g., from a standard). We furthermore present a technique to automatically derive test-cases to point out found deviations on the actual system.We also present a method to create abstract cybersecurity test case specifications from semi-formal threat models using attack trees. 

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  • 2.
    Marksteiner, Stefan
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. AVL List GmbH, Austria.
    Priller, Peter
    AVL List GmbH, Austria.
    Wolf, Markus
    AVL List GmbH, Austria.
    Approaches for Automating Cybersecurity Testing of Connected Vehicles2024In: Intelligent Secure Trustable Things / [ed] M. Karner et al., Cham: Springer, 2024Chapter in book (Refereed)
    Abstract [en]

    Vehicles are on the verge building highly networked and interconnected systems with each other. Thisrequires open architectures with standardized interfaces. These interfaces provide huge surfaces forpotential threats from cyber attacks. Regulators therefore demand to mitigate these risks using structuredsecurity engineering processes. Testing the effectiveness of this measures, on the other hand, is lessstandardized. To fill this gap, this book chapter contains an approach for structured and comprehensivecybersecurity testing of contemporary vehicular systems. It gives an overview of how to define securesystems and contains specific approaches for (semi-)automated cybersecurity testing of vehicular systems,including model-based testing and the description of an automated platform for executing tests.

  • 3.
    Marksteiner, Stefan
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Avl List GmbH, Graz, Austria.
    Schmittner, C.
    Ait Austrian Institute of Technology GmbH, Vienna, Austria.
    Christl, K.
    Ait Austrian Institute of Technology GmbH, Vienna, Austria.
    Nickovic, D.
    Ait Austrian Institute of Technology GmbH, Vienna, Austria.
    Sjödin, Mikael
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sirjani, Marjan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    From TARA to Test: Automated Automotive Cybersecurity Test Generation Out of Threat Modeling2023In: Proceedings: CSCS 2023 - 7th ACM Computer Science in Cars Symposium, Association for Computing Machinery, Inc , 2023Conference paper (Refereed)
    Abstract [en]

    The United Nations Economic Commission for Europe (UNECE) demands the management of cyber security risks in vehicle design and that the effectiveness of these measures is verified by testing. Generally, with rising complexity and openness of systems via software-defined vehicles, verification through testing becomes a very important for security assurance. This mandates the introduction of industrial-grade cybersecurity testing in automotive development processes. Currently, the automotive cybersecurity testing procedures are not specified or automated enough to be able to deliver tests in the amount and thoroughness needed to keep up with that regulation, let alone doing so in a cost-efficient manner. This paper presents a methodology to automatically generate technology-agnostic test scenarios from the results of threat analysis and risk assessment (TARA) process. Our approach is to transfer the resulting threat models into attack trees and label their edges using actions from a domain-specific language (DSL) for attack descriptions. This results in a labelled transitions system (LTS), in which every labelled path intrinsically forms a test scenario. In addition, we include the concept of Cybersecurity Assurance Levels (CALs) and Targeted Attack Feasibility (TAF) into testing by assigning them as costs to the attack path. This abstract test scenario can be compiled into a concrete test case by augmenting it with implementation details. Therefore, the efficacy of the measures taken because of the TARA can be verified and documented. As TARA is a de-facto mandatory step in the UNECE regulation and the relevant ISO standard, automatic test generation (also mandatory) out of it could mean a significant improvement in efficiency, as two steps could be done at once.

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