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Survey and Classification of Automotive Security Attacks

Institute of Energy Efficient Mobility (IEEM), University of Applied Sciences, Moltkestrasse 30, 76133 Karlsruhe, Germany
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These authors contributed equally to this work.
Information 2019, 10(4), 148; https://doi.org/10.3390/info10040148
Received: 1 April 2019 / Accepted: 16 April 2019 / Published: 19 April 2019
(This article belongs to the Section Information and Communications Technology)
Due to current development trends in the automotive industry towards stronger connected and autonomous driving, the attack surface of vehicles is growing which increases the risk of security attacks. This has been confirmed by several research projects in which vehicles were attacked in order to trigger various functions. In some cases these functions were critical to operational safety. To make automotive systems more secure, concepts must be developed that take existing attacks into account. Several taxonomies were proposed to analyze and classify security attacks. However, in this paper we show that the existing taxonomies were not designed for application in the automotive development process and therefore do not provide enough degree of detail for supporting development phases such as threat analysis or security testing. In order to be able to use the information that security attacks can provide for the development of security concepts and for testing automotive systems, we propose a comprehensive taxonomy with degrees of detail which addresses these tasks. In particular, our proposed taxonomy is designed in such a wa, that each step in the vehicle development process can leverage it. View Full-Text
Keywords: automotive security; security attacks; classification; taxonomy automotive security; security attacks; classification; taxonomy
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Sommer, F.; Dürrwang, J.; Kriesten, R. Survey and Classification of Automotive Security Attacks. Information 2019, 10, 148.

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