Social Engineering Exploits in Automotive Software Security: Modeling Human-targeted Attacks with SAM

• Security cannot be implemented into a system retrospectively without considerable effort, so security must be takeninto consideration already at the beginning of the system development. The engineering of automotive softwareis by no means an exception to this rule. For addressing automotive security, the AUTOSAR and EAST-ADLstandards for domain-specific system and component modeling provide the central foundation as a start. The EASTADLextension SAM enables fully integrated security modeling for traditional feature-targeted attacks. Due to theCOVID-19 pandemic, the number of cyber-attacks has increased tremendously and of these, about 98 percent arebased on social engineering attacks. These social engineering attacks exploit vulnerabilities in human behaviors,rather than vulnerabilities in a system, to inflict damage. And these social engineering attacks also play a relevantbut nonetheless regularly neglected role for automotive software. The contribution of this paper is a novel modelingconcept for social engineering attacks and their criticality assessment integrated into a general automotive softwaresecurity modeling approach. This makes it possible to relate social engineering exploits with feature-related attacks.To elevate the practical usage, we implemented an integration of this concept into the established, domain-specificmodeling tool MetaEdit+. The tool support enables collaboration between stakeholders, calculates vulnerabilityscores, and enables the specification of security objectives and measures to eliminate vulnerabilities.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

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