Security Compliance in Model-driven Development of Software Systems in Presence of Long-Term Evolution and Variants

Peldszus, Sven Matthias

ISBN 10: 3658376643 / ISBN 13: 9783658376642

Published by Springer Vieweg, 2022

About this Item

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Bibliographic Details

• Title: Security Compliance in Model-driven Development of Software Systems in Presence of Long-Term Evolution and Variants
• Publisher: Springer Vieweg
• Publication Date: 2022
• Language: English
• ISBN 10: 3658376643
• ISBN 13: 9783658376642
• Binding: Soft cover
• Condition: Good

About this title

Synopsis

For ensuring a software system's security, it is vital to keep up with changing security precautions, attacks, and mitigations. Although model-based development enables addressing security already at design-time, design models are often inconsistent with the implementation or among themselves. An additional burden are variants of software systems. To ensure security in this context, we present an approach based on continuous automated change propagation, allowing security experts to specify security requirements on the most suitable system representation. We automatically check all system representations against these requirements and provide security-preserving refactorings for preserving security compliance. For both, we show the application to variant-rich software systems. To support legacy systems, we allow to reverse-engineer variability-aware UML models and semi-automatically map existing design models to the implementation. Besides evaluations of the individual contributions, we demonstrate the approach in two open-source case studies, the iTrust electronics health records system and the Eclipse Secure Storage.

About the Author

Since 2016, Sven Matthias Peldszus has been working as a research associate at the University of Koblenz-Landau and joined the Ruhr University Bochum after defending this thesis. His research interests include continuous tracing of non-functional requirements over the entire software life cycle and software quality analysis in variant-rich software systems.