How Dataflow Diagrams Impact Software Security Analysis: an Empirical Experiment
Models of software systems are used throughout the software development lifecycle. Dataflow diagrams (DFDs), in particular, are well-established resources for security analysis. Many techniques, such as threat modelling, are based on DFDs of the analysed application. However, their impact on the performance of analysts in a security analysis setting has not been explored before. In this paper, we present the findings of an empirical experiment conducted to investigate this effect. Following a within-groups design, participants were asked to solve security-relevant tasks for a given microservice application. In the control condition, the participants had to examine the source code manually. In the model-supported condition, they were additionally provided a DFD of the analysed application and traceability information linking model items to artefacts in source code. We found that the participants (n = 24) performed significantly better in answering the analysis tasks correctly in the model-supported condition (41% increase in analysis correctness). Further, participants who reported using the provided traceability information performed better in giving evidence for their answers (315% increase in correctness of evidence). Finally, we identified three open challenges of using DFDs for security analysis based on the insights gained in the experiment.
Top- Schneider, Simon
- Ferreyra, Nicolas E. Diaz
- Quéval, Pierre-Jean
- Simhandl, Georg
- Zdun, Uwe
- Scandariato, Riccardo
Category |
Paper in Conference Proceedings or in Workshop Proceedings (Paper) |
Event Title |
31st IEEE International Conference on Software Analysis, Evolution and Reengineering 2024 |
Divisions |
Software Architecture |
Subjects |
Software Engineering |
Event Location |
Rovaniemi, Finland |
Event Type |
Conference |
Event Dates |
12 - 15 March 2024 |
Date |
2024 |
Export |