Data-flow-based adaption of the System-Theoretic Process Analysis for Security (STPA-Sec).
Jinghua YuStefan WagnerFeng LuoPublished in: PeerJ. Computer science (2021)
Security analysis is an essential activity in security engineering to identify potential system vulnerabilities and specify security requirements in the early design phases. Due to the increasing complexity of modern systems, traditional approaches lack the power to identify insecure incidents caused by complex interactions among physical systems, human and social entities. By contrast, the System-Theoretic Process Analysis for Security (STPA-Sec) approach views losses as resulting from interactions, focuses on controlling system vulnerabilities instead of external threats, and is applicable for complex socio-technical systems. However, the STPA-Sec pays less attention to the non-safety but information-security issues (e.g., data confidentiality) and lacks efficient guidance for identifying information security concepts. In this article, we propose a data-flow-based adaption of the STPA-Sec (named STPA-DFSec) to overcome the mentioned limitations and elicit security constraints systematically. We use the STPA-DFSec and STPA-Sec to analyze a vehicle digital key system and investigate the relationship and differences between both approaches, their applicability, and highlights. To conclude, the proposed approach can identify information-related problems more directly from the data processing aspect. As an adaption of the STPA-Sec, it can be used with other STPA-based approaches to co-design systems in multi-disciplines under the unified STPA framework.
Keyphrases
- global health
- electronic health record
- mental health
- public health
- big data
- healthcare
- physical activity
- magnetic resonance
- health information
- endothelial cells
- machine learning
- patient safety
- data analysis
- risk assessment
- deep learning
- artificial intelligence
- contrast enhanced
- drug induced
- induced pluripotent stem cells