KGSecConfig: A Knowledge Graph Based Approach for Secured Container Orchestrator Configuration
Mubin Ul Haque, M. Mehdi Kholoosi, and M. Ali Babar

TL;DR
This paper introduces KGSecConfig, a knowledge graph-based system that automates and improves the security configuration process for container orchestrators like Kubernetes and Docker, reducing errors and enhancing security.
Contribution
The paper presents a novel knowledge graph approach for automating security configuration in container orchestrators, integrating heterogeneous data sources for improved security management.
Findings
Achieved 0.98 accuracy in configuration option extraction.
Achieved 0.94 accuracy in concept extraction.
Demonstrated automated mitigation of misconfigurations in Kubernetes.
Abstract
Container Orchestrator (CO) is a vital technology for managing clusters of containers, which may form a virtualized infrastructure for developing and operating software systems. Like any other software system, securing CO is critical, but can be quite challenging task due to large number of configurable options. Manual configuration is not only knowledge intensive and time consuming, but also is error prone. For automating security configuration of CO, we propose a novel Knowledge Graph based Security Configuration, KGSecConfig, approach. Our solution leverages keyword and learning models to systematically capture, link, and correlate heterogeneous and multi-vendor configuration space in a unified structure for supporting automation of security configuration of CO. We implement KGSecConfig on Kubernetes, Docker, Azure, and VMWare to build secured configuration knowledge graph. Our…
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Taxonomy
TopicsSoftware System Performance and Reliability · Software Engineering Research · Software Engineering Techniques and Practices
