Compositional Security Analysis of Dynamic Component-based Systems

To reason about and enforce security in dynamic software systems, automated analysis and verification approaches are required. However, such approaches often encounter scalability issues, particularly when employed for runtime analysis, which is necessary in software systems with dynamically changing architectures, such as self-adaptive systems. In this work, we propose an automated formal approach for security analysis of component-based systems with dynamic architectures. This approach leverages formal abstraction and incremental analysis techniques to reduce the complexity of runtime analysis. We have implemented and evaluated our approach against ZNN, a widely known self-adaptive system exemplar. Our experimental results demonstrate the effectiveness of our approach in addressing scalability issues.

Authors

Institutions

Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3691620.3695499
Citations
1
Primary Topic
Security and Verification in Computing
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Compositional Security Analysis of Dynamic Component-based Systems

Charilaos Skandylas, Narges Khakpour
1 citations
Security and Verification in Computing
0.35
article

Compositional Security Analysis of Dynamic Component-based Systems

Charilaos Skandylas, Narges Khakpour
article en
1 citations

Abstract

To reason about and enforce security in dynamic software systems, automated analysis and verification approaches are required. However, such approaches often encounter scalability issues, particularly when employed for runtime analysis, which is necessary in software systems with dynamically changing architectures, such as self-adaptive systems. In this work, we propose an automated formal approach for security analysis of component-based systems with dynamic architectures. This approach leverages formal abstraction and incremental analysis techniques to reduce the complexity of runtime analysis. We have implemented and evaluated our approach against ZNN, a widely known self-adaptive system exemplar. Our experimental results demonstrate the effectiveness of our approach in addressing scalability issues.

Linköping University (SE), Linnaeus University (SE), Newcastle University (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 33%
Security and Verification in Computing
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.