TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publication References
  4. Automatic extraction of security-rich dataflow diagrams for microservice applications written in Java
 
Options

Automatic extraction of security-rich dataflow diagrams for microservice applications written in Java

Publikationstyp
Journal Article
Date Issued
2023-08
Sprache
English
Author(s)
Schneider, Simon  
Scandariato, Riccardo  
Institut
Software Security E-22  
TORE-URI
http://hdl.handle.net/11420/15338
Journal
The journal of systems and software  
Volume
202
Article Number
111722
Citation
Journal of Systems and Software 202: 111722 (2023-08)
Publisher DOI
10.1016/j.jss.2023.111722
Scopus ID
2-s2.0-85158001078
Dataflow diagrams (DFDs) are a valuable asset for securing applications, as they are the starting point for many security assessment techniques. Their creation, however, is often done manually, which is time-consuming and introduces problems concerning their correctness. Furthermore, as applications are continuously extended and modified in CI/CD pipelines, the DFDs need to be kept in sync, which is also challenging. In this paper, we present a novel, tool-supported technique to automatically extract DFDs from the implementation code of microservices. The technique parses source code and configuration files in search for keywords that are used as evidence for the model extraction. Our approach uses a novel technique that iteratively detects new keywords, thereby snowballing through an application's codebase. Coupled with other detection techniques, it produces a fully-fledged DFD enriched with security-relevant annotations. The extracted DFDs further provide full traceability between model items and code snippets. We evaluate our approach and the accompanying prototype for applications written in Java on a manually curated dataset of 17 open-source applications. In our testing set of applications, we observe an overall precision of 93% and recall of 85%. The dataset created for the evaluation is openly released to the research community, as additional contribution of this work.
Subjects
Architecture reconstruction
Automatic extraction
Dataflow diagram
Feature detection
Microservices
Security
TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback