Observability and Incident Response in Managed Serverless Environments Using Ontology-Based Log Monitoring

In a fully managed serverless environment, the cloud service provider is responsible for securing the cloud infrastructure, thereby reducing the operational and maintenance efforts of application developers. However, this environment limits the use of existing cybersecurity frameworks and tools, whi...

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Hauptverfasser: Ben-Shimol, Lavi, Grolman, Edita, Elyashar, Aviad, Maimon, Inbar, Mimran, Dudu, Brodt, Oleg, Strassmann, Martin, Lehmann, Heiko, Elovici, Yuval, Shabtai, Asaf
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Sprache:eng
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Zusammenfassung:In a fully managed serverless environment, the cloud service provider is responsible for securing the cloud infrastructure, thereby reducing the operational and maintenance efforts of application developers. However, this environment limits the use of existing cybersecurity frameworks and tools, which reduces observability and situational awareness capabilities (e.g., risk assessment, incident response). In addition, existing security frameworks for serverless applications do not generalize well to all application architectures and usually require adaptation, specialized expertise, etc. for use in fully managed serverless environments. In this paper, we introduce a three-layer security scheme for applications deployed in fully managed serverless environments. The first two layers involve a unique ontology based solely on serverless logs which is used to transform them into a unified application activity knowledge graph. In the third layer, we address the need for observability and situational awareness capabilities by implementing two situational awareness tools that utilizes the graph-based representation: 1) An incident response dashboard that leverages the ontology to visualize and examine application activity logs in the context of cybersecurity alerts. Our user study showed that the dashboard enabled participants to respond more accurately and quickly to new security alerts than the baseline tool. 2) A criticality of asset (CoA) risk assessment framework that enables efficient expert-based prioritization in cybersecurity contexts.
DOI:10.48550/arxiv.2405.07172