Automating the early detection of security design flaws
Paper i proceeding, 2020

Security by design is a key principle for realizing secure software systems and it is advised to hunt for security flaws from the very early stages of development. At design-time, security analysis is often performed manually by means of either threat modeling or expert-based design inspections. However, when leveraging the wide range of established knowledge bases on security design flaws (e.g., CWE, CAWE), these manual assessments become too time consuming, error-prone, and infeasible in the context of contemporary development practices with frequent iterations. This paper focuses on design inspection and explores the potential for automating the application of inspection rules to speed up the security analysis.

The contributions of this paper are: (i) the creation of a publicly available data set consisting of 26 design models annotated with security flaws, (ii) an automated approach for following inspection guidelines using model query patterns, and (iii) an empirical comparison of the results from this automated approach with those from manual inspection. Even though our results show that a complete automation of the security design flaw detection is hard to achieve, we find that some flaws (e.g., insecure data exposure) are more amenable to automation. Compared to manual analysis techniques, our results are encouraging and suggest that the automated technique could guide security analysts towards a more complete inspection of the software design, especially for large models.

security flaw

automation

design flaw detection

security-by-design

empirical software engineering

secure design

Författare

Katja Tuma

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Cyber Physical Systems

Laurens Sion

KU Leuven

Riccardo Scandariato

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Cyber Physical Systems

Koen Yskout

KU Leuven

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems

MODELS '20 332-342

International Conference on Model Driven Engineering Languages and Systems, MODELS
Virtual Event, Canada,

Ämneskategorier

Annan data- och informationsvetenskap

Övrig annan teknik

Systemvetenskap

DOI

10.1145/3365438.3410954

Mer information

Skapat

2020-11-16