Publikationen

Autor	Chevalier, Yannick; Rieke, Roland; Fenzl, Florian; Chechulin, Andrey; Kotenko, Igor
Datum	2020
Art	Conference Paper
Abstrakt	Growing connectivity of vehicles induces increasing attack surfaces and thus the demand for a sophisticated security strategy. One part of such a strategy is to accurately detect intrusive behavior in an in-vehicle network. Therefore, we built a log analyzer in C that focused on payload bytes having either a small set of different values or a small set of possible changes. While being an order of magnitude faster, the accuracy of the results obtained is at least comparable with results obtained using standard machine learning techniques. Thus, this approach is an interesting option for implementation within in-vehicle embedded systems. Another important aspect is that the explainability of the results is better compared to deep learning systems.
Konferenz	International Symposium on Intelligent Distributed Computing (IDC) 2019
Projekt	VITAF
Url	https://publica.fraunhofer.de/handle/publica/406441

ECU-Secure: Characteristic Functions for In-Vehicle Intrusion Detection