Pith. sign in

REVIEW 1 cited by

How Dataflow Diagrams Impact Software Security Analysis: an Empirical Experiment

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2401.04446 v1 pith:R5SWKIN3 submitted 2024-01-09 cs.SE

classification cs.SE
keywords analysisparticipantssecurityapplicationconditiondfdsexperimentsoftware
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. ThreMoLIA: Threat Modeling of Large Language Model-Integrated Applications

    cs.CR 2025-04 conditional novelty 4.0 of 10

    The authors propose an LLM-and-RAG-based threat modeling tool for LLM-integrated applications and report one early, unvalidated ChatGPT pilot as preliminary motivation.

Pith tools