Abstract
In this work, methods are presented that allow a comparison between control flow paths. The intended use cases for these methods are weak points and bug detection. In existing work, control flow graphs have always been compared with each other to achieve those goals. Nevertheless, vulnerabilities or bugs can be hidden in completely different contexts, i.e. in different parts of the program. Therefore, this work deals with the extraction, coding and comparison of control flow paths. This is because the path of a vulnerability or bug in which the instructions are executed is always similar.
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Schäfer, A., Amme, W. (2021). Detecting Control Flow Similarities Using Machine Learning Techniques. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1252. Springer, Cham. https://doi.org/10.1007/978-3-030-55190-2_48
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DOI: https://doi.org/10.1007/978-3-030-55190-2_48
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