Title: Security concept and evaluation of an off-highway electronic control unit
Other Titles: Security Konzept und Evaluierung einer Off-Highway Electronic Control Unit
Language: English
Authors: Reier, Lukas 
Qualification level: Diploma
Advisor: Steiner, Wilfried 
Issue Date: 2020
Number of Pages: 65
Qualification level: Diploma
Mobile machinery and vehicles used for agricultural, construction, mining, and material handling purposes are currently experiencing a rapid transition from exclusively mechanical to cyber-physical systems. In order to increase the efficiency and productivity of such off-highway vehicles, electronic components with advanced connectivity are being integrated. However, these electronic systems and their interfaces introduce new cyber-security vulnerabilities. The off-highway industry is experienced in developing safe systems, but security is an emerging new field with less practice. The aim of this master thesis is to closely examine an example use case for an off-highway electronic control unit (ECU). Based on the identified cyber-security threats identified by a Threat Analysis and Risk Assessment (TARA), a security concept is developed, implemented and evaluated. The security requirements resulting from the risk assessment are refined and solutions to minimize the threats and increase cyber-security are presented. Appropriate cryptographic primitives for such an embedded system are selected. For the off-highway ECU an embedded software solution is developed. The ECU contains an automotive microprocessor with an additional security co-processor. The software solution consists of two programs, one executed on the main core of the microprocessor and one running on the microprocessor’s security co-processor. The software implemented for this thesis aims to mitigate the security threats and to make use of hardware accelerations provided by the security co-processor. The performance of the implementation is evaluated.
Keywords: off-highway; electronic control unit; ECU; security; communication; diagnosis
URI: https://doi.org/10.34726/hss.2020.75480
DOI: 10.34726/hss.2020.75480
Library ID: AC15749773
Organisation: E191 - Institut für Computer Engineering 
Publication Type: Thesis
Appears in Collections:Thesis

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